Observational studies have shown that physical activity levels are inversely, and sedentary behaviours are positively, associated with colorectal cancer risk; however, whether these relationships are consistent across anatomical subsites is uncertain.

Methods:

We investigated the associations between colorectal cancer and physical activity (metabolic equivalents (METs)-hours per week), and indicators of sedentary behaviour (television watching time and time spent using computers) among 430 584 men and women enroled in the UK Biobank. Multivariable hazard ratios (HRs) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models.

Results:

After a median follow-up time of 5.6 years, 2391 incident colorectal cancer cases were recorded. High (60-MET-hours per week) vs low (<10-MET-hours per week) total physical activity was associated with a lower colon cancer risk (HR=0.84, 95% CI: 0.72–0.98; p-trend=0.04), with comparable relationships observed for proximal and distal colon tumours, but no association for rectal cancer. Higher levels of television watching time were associated with greater colon cancer risk (HR for 5 h per day vs 1 h per day=1.32, 95% CI: 1.04–1.68; p-trend=0.007). Time spent using computers was not associated with colorectal cancer risk.

Observational studies have shown that physical activity levels are inversely, and sedentary behaviours are positively, associated with colorectal cancer risk; however, whether these relationships are consistent across anatomical subsites is uncertain.

Methods:

We investigated the associations between colorectal cancer and physical activity (metabolic equivalents (METs)-hours per week), and indicators of sedentary behaviour (television watching time and time spent using computers) among 430 584 men and women enroled in the UK Biobank. Multivariable hazard ratios (HRs) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models.

Results:

After a median follow-up time of 5.6 years, 2391 incident colorectal cancer cases were recorded. High (60-MET-hours per week) vs low (<10-MET-hours per week) total physical activity was associated with a lower colon cancer risk (HR=0.84, 95% CI: 0.72–0.98; p-trend=0.04), with comparable relationships observed for proximal and distal colon tumours, but no association for rectal cancer. Higher levels of television watching time were associated with greater colon cancer risk (HR for 5 h per day vs 1 h per day=1.32, 95% CI: 1.04–1.68; p-trend=0.007). Time spent using computers was not associated with colorectal cancer risk.

The effect of menopausal hormone therapy (MHT)–previously known as hormone replacement therapy–on cardiovascular health remains unclear and controversial. This cross-sectional study examined the impact of MHT on left ventricular (LV) and left atrial (LA) structure and function, alterations in which are markers of subclinical cardiovascular disease, in a population-based cohort.

Methods

Post-menopausal women who had never used MHT and those who had used MHT ≥3 years participating in the UK Biobank who had undergone cardiovascular magnetic resonance (CMR) imaging and free of known cardiovascular disease were included. Multivariable linear regression was performed to examine the relationship between cardiac parameters and MHT use ≥3 years. To explore whether MHT use on each of the cardiac outcomes differed by age, multivariable regression models were constructed with a cross-product of age and MHT fitted as an interaction term.

The effect of menopausal hormone therapy (MHT)–previously known as hormone replacement therapy–on cardiovascular health remains unclear and controversial. This cross-sectional study examined the impact of MHT on left ventricular (LV) and left atrial (LA) structure and function, alterations in which are markers of subclinical cardiovascular disease, in a population-based cohort.

Methods

Post-menopausal women who had never used MHT and those who had used MHT ≥3 years participating in the UK Biobank who had undergone cardiovascular magnetic resonance (CMR) imaging and free of known cardiovascular disease were included. Multivariable linear regression was performed to examine the relationship between cardiac parameters and MHT use ≥3 years. To explore whether MHT use on each of the cardiac outcomes differed by age, multivariable regression models were constructed with a cross-product of age and MHT fitted as an interaction term.

MHT use was not associated with adverse, subclinical changes in cardiac structure and function. Indeed, significantly smaller LV and LA chamber volumes were observed which have been linked to favourable cardiovascular outcomes. These findings represent a novel approach to examining MHT’s effect on the cardiovascular system.

@article{Beaumont2018,
title = {Genome-wide association study of offspring birth weight in 86,577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics},
author = {Robin N Beaumont and et al. },
url = {https://academic.oup.com/hmg/advance-article/doi/10.1093/hmg/ddx429/4788598},
year = {2018},
date = {2018-03-01},
journal = {Human Molecular Genetics},
abstract = {Genome-wide association studies (GWAS) of birth weight have focused on fetal genetics, while relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86,577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P<5x10−8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.},
note = {Robin N Beaumont and Nicole M Warrington and Alana Cavadino and Jessica Tyrrell and Michael Nodzenski and Momoko Horikoshi and Frank Geller and Ronny Myhre and Rebecca C Richmond and Lavinia Paternoster and Jonathan P Bradfield and Eskil Kreiner-Møller and Ville Huikari and Sarah Metrustry and Kathryn L Lunetta and Jodie N Painter and Jouke-Jan Hottenga and Catherine Allard and Sheila J Barton and Ana Espinosa and Julie A Marsh and Catherine Potter and Ge Zhang and Wei Ang and Diane J Berry and Luigi Bouchard and Shikta Das and Hakon Hakonarson and Jani Heikkinen and Øyvind Helgeland and Berthold Hocher and Albert Hofman and Hazel M Inskip and Samuel E Jones and Manolis Kogevinas and Penelope A Lind and Letizia Marullo and Sarah E Medland and Anna Murray and Jeffrey C Murray and Pål R Njølstad and Ellen A Nohr and Christoph Reichetzeder and Susan M Ring and Katherine S Ruth and Loreto Santa-Marina and Denise M Scholtens and Sylvain Sebert and Verena Sengpiel and Marcus A Tuke and Marc Vaudel and Michael N Weedon and Gonneke Willemsen and Andrew R Wood and Hanieh Yaghootkar and Louis J Muglia and Meike Bartels and Caroline L Relton and Craig E Pennell and Leda Chatzi and Xavier Estivill and John W Holloway and Dorret I Boomsma and Grant W Montgomery and Joanne M Murabito and Tim D Spector and Christine Power and Marjo-Ritta and Järvelin Hans Bisgaard and Struan FA Grant and Thorkild IA Sørensen and Vincent W Jaddoe and Bo Jacobsson and Mads Melbye and Mark I McCarthy and Andrew T Hattersley and M Geoffrey Hayes and Timothy M Frayling and Marie-France Hivert and Janine F Felix and Elina Hyppönen and William L Lowe Jr and David M Evans and Debbie A Lawlor },
keywords = {7036, birth weight, featured, fetal, genetics},
pubstate = {published},
tppubtype = {article}
}

Genome-wide association studies (GWAS) of birth weight have focused on fetal genetics, while relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86,577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P<5x10−8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

We examined whether seasonal variations in depressive symptoms occurred independently of demographic and lifestyle factors, and were related to change in day length and/or outdoor temperature.

Methods

In a cross-sectional analysis of >150,000 participants of the UK Biobank cohort, we used the cosinor method to assess evidence of seasonality of a total depressive symptoms score and of low mood, anhedonia, tenseness and tiredness scores in women and men. Associations of depressive symptoms with day length and mean outdoor temperature were then examined.

Results

Seasonality of total depressive symptom scores, anhedonia and tiredness scores was observed in women but not men, with peaks in winter. In women, increased day length was associated with reduced low mood and anhedonia scores, independent of demographic and lifestyle factors. For women, longer day length was associated with increased tiredness. Associations with day length were not independent of the average outdoor temperature preceding assessment.

Limitations

This was a cross-sectional investigation – longitudinal studies of within-subject seasonal variation in mood are necessary. Outcome measures relied on self-report and measured only a subset of depressive symptoms.

Conclusion

This large, population-based study provides evidence of seasonal variation in depressive symptoms in women. Shorter days were associated with increased feelings of low mood and anhedonia in women. Clinicians should be aware of these population-level sex differences in seasonal mood variations in order to aid recognition and treatment of depression and subclinical depressive symptoms.},
keywords = {6553, depression, men, seasonality, Women},
pubstate = {published},
tppubtype = {article}
}

We examined whether seasonal variations in depressive symptoms occurred independently of demographic and lifestyle factors, and were related to change in day length and/or outdoor temperature.

Methods

In a cross-sectional analysis of >150,000 participants of the UK Biobank cohort, we used the cosinor method to assess evidence of seasonality of a total depressive symptoms score and of low mood, anhedonia, tenseness and tiredness scores in women and men. Associations of depressive symptoms with day length and mean outdoor temperature were then examined.

Results

Seasonality of total depressive symptom scores, anhedonia and tiredness scores was observed in women but not men, with peaks in winter. In women, increased day length was associated with reduced low mood and anhedonia scores, independent of demographic and lifestyle factors. For women, longer day length was associated with increased tiredness. Associations with day length were not independent of the average outdoor temperature preceding assessment.

Limitations

This was a cross-sectional investigation – longitudinal studies of within-subject seasonal variation in mood are necessary. Outcome measures relied on self-report and measured only a subset of depressive symptoms.

Conclusion

This large, population-based study provides evidence of seasonal variation in depressive symptoms in women. Shorter days were associated with increased feelings of low mood and anhedonia in women. Clinicians should be aware of these population-level sex differences in seasonal mood variations in order to aid recognition and treatment of depression and subclinical depressive symptoms.

Heart rate (HR) responds to exercise by increasing during exercise and recovering after exercise. As such, HR is an important predictor of mortality that researchers believe is modulated by the autonomic nervous system. However, the mechanistic basis underlying inter-individual differences has yet to be explained. Here, we perform a large-scale genome-wide analysis of HR increase and HR recovery in 58,818 UK Biobank individuals. Twenty-five independent SNPs in 23 loci are identified to be associated (p < 8.3 × 10−9) with HR increase or HR recovery. A total of 36 candidate causal genes are prioritized that are enriched for pathways related to neuron biology. No evidence is found of a causal relationship with mortality or cardiovascular diseases. However, a nominal association with parental lifespan requires further study. In conclusion, the findings provide new biological and clinical insight into the mechanistic underpinnings of HR response to exercise. The results also underscore the role of the autonomous nervous system in HR recovery.

@article{Peters2018b,
title = {Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank},
author = {Sanne A. E. Peters and Sophie H. Bots and Mark Woodward},
url = {http://jaha.ahajournals.org/content/7/5/e008507},
year = {2018},
date = {2018-02-28},
journal = {Journal of American Heart Association},
abstract = {Background There are substantial differences in the distribution of adipose tissue between women and men. We assessed the sex‐specific relationships and their differences between measures of general and central adiposity and the risk of incident myocardial infarction (MI).

Methods and Results Between 2006 and 2010, the UK Biobank recruited over 500 000 participants aged 40 to 69 years across the United Kingdom. During 7 years of follow‐up, 5710 cases of MI (28% women) were recorded among 265 988 women and 213 622 men without a history of cardiovascular disease at baseline. Cox regression models yielded adjusted hazard ratios for MI associated with body mass index, waist circumference, waist‐to‐hip ratio, and waist‐to‐height ratio. There was an approximate log‐linear relationship between measures of general and central adiposity and the risk of MI in both sexes. A 1‐SD higher in body mass index, waist circumference, waist‐to‐hip ratio, and waist‐to‐height ratio, respectively, were associated with hazard ratios (confidence intervals) for MI of 1.22 (1.17; 1.28), 1.35 (1.28; 1.42), 1.49 (1.39; 1.59), and 1.34 (1.27; 1.40) in women and of 1.28 (1.23; 1.32), 1.28 (1.23; 1.33), 1.36 (1.30; 1.43), and 1.33 (1.28; 1.38) in men. The corresponding women‐to‐men ratios of hazard ratios were 0.96 (0.91; 1.02), 1.07 (1.00; 1.14), 1.15 (1.06; 1.24), and 1.03 (0.97; 1.09).

Conclusions Although general and central adiposity measures each have profound deleterious effects on the risk of MI in both sexes, a higher waist circumference and waist‐to‐hip ratio conferred a greater excess risk of MI in women than in men. Waist‐to‐hip ratio was more strongly associated with the risk of MI than body mass index in both sexes, especially in women.},
keywords = {2495, BMI, featured, heart disease},
pubstate = {published},
tppubtype = {article}
}

Background There are substantial differences in the distribution of adipose tissue between women and men. We assessed the sex‐specific relationships and their differences between measures of general and central adiposity and the risk of incident myocardial infarction (MI).

Methods and Results Between 2006 and 2010, the UK Biobank recruited over 500 000 participants aged 40 to 69 years across the United Kingdom. During 7 years of follow‐up, 5710 cases of MI (28% women) were recorded among 265 988 women and 213 622 men without a history of cardiovascular disease at baseline. Cox regression models yielded adjusted hazard ratios for MI associated with body mass index, waist circumference, waist‐to‐hip ratio, and waist‐to‐height ratio. There was an approximate log‐linear relationship between measures of general and central adiposity and the risk of MI in both sexes. A 1‐SD higher in body mass index, waist circumference, waist‐to‐hip ratio, and waist‐to‐height ratio, respectively, were associated with hazard ratios (confidence intervals) for MI of 1.22 (1.17; 1.28), 1.35 (1.28; 1.42), 1.49 (1.39; 1.59), and 1.34 (1.27; 1.40) in women and of 1.28 (1.23; 1.32), 1.28 (1.23; 1.33), 1.36 (1.30; 1.43), and 1.33 (1.28; 1.38) in men. The corresponding women‐to‐men ratios of hazard ratios were 0.96 (0.91; 1.02), 1.07 (1.00; 1.14), 1.15 (1.06; 1.24), and 1.03 (0.97; 1.09).

Conclusions Although general and central adiposity measures each have profound deleterious effects on the risk of MI in both sexes, a higher waist circumference and waist‐to‐hip ratio conferred a greater excess risk of MI in women than in men. Waist‐to‐hip ratio was more strongly associated with the risk of MI than body mass index in both sexes, especially in women.

Traditionally, medical discoveries are made by observing associations, making hypotheses from them and then designing and running experiments to test the hypotheses. However, with medical images, observing and quantifying associations can often be difficult because of the wide variety of features, patterns, colours, values and shapes that are present in real data. Here, we show that deep learning can extract new knowledge from retinal fundus images. Using deep-learning models trained on data from 284,335 patients and validated on two independent datasets of 12,026 and 999 patients, we predicted cardiovascular risk factors not previously thought to be present or quantifiable in retinal images, such as age (mean absolute error within 3.26 years), gender (area under the receiver operating characteristic curve (AUC) = 0.97), smoking status (AUC = 0.71), systolic blood pressure (mean absolute error within 11.23 mmHg) and major adverse cardiac events (AUC = 0.70). We also show that the trained deep-learning models used anatomical features, such as the optic disc or blood vessels, to generate each prediction.

@article{Gallacher2018,
title = {Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants},
author = {Katie I. Gallacher and Ross McQueenie and Barbara Nicholl and Bhuatesh D. Jani and Duncan Lee and Frances S. Mair},
url = {https://jcomorbidity.com/index.php/test/article/view/129},
year = {2018},
date = {2018-02-19},
journal = {Journal of Comorbidity },
abstract = {Background: Multimorbidity is common in stroke, but the risk factors and effects on mortality remain poorly understood. Objective: To examine multimorbidity and its associations with sociodemographic/lifestyle risk factors and all-cause mortality in UK Biobank participants with stroke or transient ischaemic attack (TIA). Design: Data were obtained from an anonymized community cohort aged 40–72 years. Overall, 42 comorbidities were self-reported by those with stroke or TIA. Relative risk ratios demonstrated associations between participant characteristics and number of comorbidities. Hazard ratios demonstrated associations between the number and type of comorbidities and all-cause mortality. Results were adjusted for age, sex, socioeconomic status, smoking, and alcohol intake. Data were linked to national mortality data. Median follow-up was 7 years. Results: Of 8,751 participants (mean age 60.9±6.7 years) with stroke or TIA, the all-cause mortality rate over 7 years was 8.4%. Over 85% reported ≥1 comorbidities. Age, socioeconomic deprivation, smoking and less frequent alcohol intake were associated with higher levels of multimorbidity. Increasing multimorbidity was associated with higher all-cause mortality. Mortality risk was double for those with ≥5 comorbidities compared to those with none. Having cancer, coronary heart disease, diabetes, or chronic obstructive pulmonary disease significantly increased mortality risk. Presence of any cardiometabolic comorbidity significantly increased mortality risk, as did any non-cardiometabolic comorbidity. Conclusions: In stroke survivors, the number of comorbidities may be a more helpful predictor of mortality than type of condition. Stroke guidelines should take greater account of comorbidities, and interventions are needed that improve outcomes for people with multimorbidity and stroke.},
keywords = {14151, mortality, risk factors, Stroke},
pubstate = {published},
tppubtype = {article}
}

Background: Multimorbidity is common in stroke, but the risk factors and effects on mortality remain poorly understood. Objective: To examine multimorbidity and its associations with sociodemographic/lifestyle risk factors and all-cause mortality in UK Biobank participants with stroke or transient ischaemic attack (TIA). Design: Data were obtained from an anonymized community cohort aged 40–72 years. Overall, 42 comorbidities were self-reported by those with stroke or TIA. Relative risk ratios demonstrated associations between participant characteristics and number of comorbidities. Hazard ratios demonstrated associations between the number and type of comorbidities and all-cause mortality. Results were adjusted for age, sex, socioeconomic status, smoking, and alcohol intake. Data were linked to national mortality data. Median follow-up was 7 years. Results: Of 8,751 participants (mean age 60.9±6.7 years) with stroke or TIA, the all-cause mortality rate over 7 years was 8.4%. Over 85% reported ≥1 comorbidities. Age, socioeconomic deprivation, smoking and less frequent alcohol intake were associated with higher levels of multimorbidity. Increasing multimorbidity was associated with higher all-cause mortality. Mortality risk was double for those with ≥5 comorbidities compared to those with none. Having cancer, coronary heart disease, diabetes, or chronic obstructive pulmonary disease significantly increased mortality risk. Presence of any cardiometabolic comorbidity significantly increased mortality risk, as did any non-cardiometabolic comorbidity. Conclusions: In stroke survivors, the number of comorbidities may be a more helpful predictor of mortality than type of condition. Stroke guidelines should take greater account of comorbidities, and interventions are needed that improve outcomes for people with multimorbidity and stroke.

CONCLUSIONS Our findings show that night shift work, especially rotating shift work including night shifts, is associated with higher type 2 diabetes odds and that the number of night shifts worked per month appears most relevant for type 2 diabetes odds. Also, shift work exposure does not modify genetic risk for type 2 diabetes, a novel finding that warrants replication.

High blood pressure (BP) is a major risk factor for cardiovascular diseases (CVDs), the leading cause of mortality worldwide. Both heritable and lifestyle risk factors contribute to elevated BP levels. We aimed to investigate the extent to which lifestyle factors could offset the effect of an adverse BP genetic profile and its effect on CVD risk.
METHODS:

We constructed a genetic risk score for high BP by using 314 published BP loci in 277 005 individuals without previous CVD from the UK Biobank study, a prospective cohort of individuals aged 40 to 69 years, with a median of 6.11 years of follow-up. We scored participants according to their lifestyle factors including body mass index, healthy diet, sedentary lifestyle, alcohol consumption, smoking, and urinary sodium excretion levels measured at recruitment. We examined the association between tertiles of genetic risk and tertiles of lifestyle score with BP levels and incident CVD by using linear regression and Cox regression models, respectively.
RESULTS:

Healthy lifestyle score was strongly associated with BP (P<10-320) for systolic and diastolic BP and CVD events regardless of the underlying BP genetic risk. Participants with a favorable in comparison with an unfavorable lifestyle (bottom versus top tertile lifestyle score) had 3.6, 3.5, and 3.6 mm Hg lower systolic BP in low, middle, and high genetic risk groups, respectively (P for interaction=0.0006). Similarly, favorable in comparison with unfavorable lifestyle showed 30%, 31%, and 33% lower risk of CVD among participants in low, middle, and high genetic risk groups, respectively (P for interaction=0.99).
CONCLUSIONS:

High blood pressure (BP) is a major risk factor for cardiovascular diseases (CVDs), the leading cause of mortality worldwide. Both heritable and lifestyle risk factors contribute to elevated BP levels. We aimed to investigate the extent to which lifestyle factors could offset the effect of an adverse BP genetic profile and its effect on CVD risk.
METHODS:

We constructed a genetic risk score for high BP by using 314 published BP loci in 277 005 individuals without previous CVD from the UK Biobank study, a prospective cohort of individuals aged 40 to 69 years, with a median of 6.11 years of follow-up. We scored participants according to their lifestyle factors including body mass index, healthy diet, sedentary lifestyle, alcohol consumption, smoking, and urinary sodium excretion levels measured at recruitment. We examined the association between tertiles of genetic risk and tertiles of lifestyle score with BP levels and incident CVD by using linear regression and Cox regression models, respectively.
RESULTS:

Healthy lifestyle score was strongly associated with BP (P<10-320) for systolic and diastolic BP and CVD events regardless of the underlying BP genetic risk. Participants with a favorable in comparison with an unfavorable lifestyle (bottom versus top tertile lifestyle score) had 3.6, 3.5, and 3.6 mm Hg lower systolic BP in low, middle, and high genetic risk groups, respectively (P for interaction=0.0006). Similarly, favorable in comparison with unfavorable lifestyle showed 30%, 31%, and 33% lower risk of CVD among participants in low, middle, and high genetic risk groups, respectively (P for interaction=0.99).
CONCLUSIONS:

Our data further support population-wide efforts to lower BP in the population via lifestyle modification. The advantages and disadvantages of disclosing genetic predisposition to high BP for risk stratification needs careful evaluation.

@article{Skaaby2018,
title = {Associations of genetic determinants of serum vitamin B12 and folate concentrations with hay fever and asthma: a Mendelian randomization meta-analysis.},
author = {T Skaaby and AE Taylor and RK Jacobsen and LT Møllehave and N Friedrich and BH Thuesen and DM Shabanzadeh and L Paternoster and U Völker and M Nauck and H Völzke and M Munafò and T Hansen and O Pedersen and T Jørgensen and N Grarup and A Linneberg},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29249824},
year = {2018},
date = {2018-02-07},
journal = {European Journal of Clinical Nutrition},
abstract = {Studies of the effect of vitamin B12 and folate on the risk of asthma and hay fever have shown inconsistent results that may be biased by reverse causation and confounding. We used a Mendelian randomization approach to examine a potential causal effect of vitamin B12 and folate on hay fever, asthma, and selected biomarkers of allergy by using 11 vitamin B12-associated single-nucleotide polymorphisms (SNPs) and 2 folate-associated SNPs as unconfounded markers.
SUBJECTS/METHODS:

We included 162,736 participants from 9 population-based studies including the UK Biobank. Results were combined in instrumental variable and meta-analyses and effects expressed as odds ratios (ORs) or estimates with 95% confidence interval (CI).
RESULTS:

Our results did not support the hypothesis that levels of vitamin B12 and folate are causally related to hay fever, asthma, or biomarkers of allergy, but we found evidence of a positive association between serum folate and serum total IgE.},
keywords = {17765, genetics},
pubstate = {published},
tppubtype = {article}
}

Studies of the effect of vitamin B12 and folate on the risk of asthma and hay fever have shown inconsistent results that may be biased by reverse causation and confounding. We used a Mendelian randomization approach to examine a potential causal effect of vitamin B12 and folate on hay fever, asthma, and selected biomarkers of allergy by using 11 vitamin B12-associated single-nucleotide polymorphisms (SNPs) and 2 folate-associated SNPs as unconfounded markers.
SUBJECTS/METHODS:

We included 162,736 participants from 9 population-based studies including the UK Biobank. Results were combined in instrumental variable and meta-analyses and effects expressed as odds ratios (ORs) or estimates with 95% confidence interval (CI).
RESULTS:

Our results did not support the hypothesis that levels of vitamin B12 and folate are causally related to hay fever, asthma, or biomarkers of allergy, but we found evidence of a positive association between serum folate and serum total IgE.

@article{Casalone2018,
title = {A novel variant in GLIS3 is associated with osteoarthritis},
author = { Elisabetta Casalone and Ioanna Tachmazidou and Eleni Zengini and Konstantinos Hatzikotoulas and Sophie Hackinger and Daniel Suveges and Julia Steinberg and Nigel William Rayner and arcOGEN Consortium and Jeremy Mark Wilkinson and Kalliope Panoutsopoulou and Eleftheria Zeggini},
url = {http://ard.bmj.com/content/early/2018/02/06/annrheumdis-2017-211848},
year = {2018},
date = {2018-02-07},
journal = {Annals of the Rheumatic diseases},
abstract = {Objectives Osteoarthritis (OA) is a complex disease, but its genetic aetiology remains poorly characterised. To identify novel susceptibility loci for OA, we carried out a genome-wide association study (GWAS) in individuals from the largest UK-based OA collections to date.

Methods We carried out a discovery GWAS in 5414 OA individuals with knee and/or hip total joint replacement (TJR) and 9939 population-based controls. We followed-up prioritised variants in OA subjects from the interim release of the UK Biobank resource (up to 12 658 cases and 50 898 controls) and our lead finding in operated OA subjects from the full release of UK Biobank (17 894 cases and 89 470 controls). We investigated its functional implications in methylation, gene expression and proteomics data in primary chondrocytes from 12 pairs of intact and degraded cartilage samples from patients undergoing TJR.

Results We detect a genome-wide significant association at rs10116772 with TJR (P=3.7×10−8; for allele A: OR (95% CI) 0.97 (0.96 to 0.98)), an intronic variant in GLIS3, which is expressed in cartilage. Variants in strong correlation with rs10116772 have been associated with elevated plasma glucose levels and diabetes.

Objectives Osteoarthritis (OA) is a complex disease, but its genetic aetiology remains poorly characterised. To identify novel susceptibility loci for OA, we carried out a genome-wide association study (GWAS) in individuals from the largest UK-based OA collections to date.

Methods We carried out a discovery GWAS in 5414 OA individuals with knee and/or hip total joint replacement (TJR) and 9939 population-based controls. We followed-up prioritised variants in OA subjects from the interim release of the UK Biobank resource (up to 12 658 cases and 50 898 controls) and our lead finding in operated OA subjects from the full release of UK Biobank (17 894 cases and 89 470 controls). We investigated its functional implications in methylation, gene expression and proteomics data in primary chondrocytes from 12 pairs of intact and degraded cartilage samples from patients undergoing TJR.

Results We detect a genome-wide significant association at rs10116772 with TJR (P=3.7×10−8; for allele A: OR (95% CI) 0.97 (0.96 to 0.98)), an intronic variant in GLIS3, which is expressed in cartilage. Variants in strong correlation with rs10116772 have been associated with elevated plasma glucose levels and diabetes.

Conclusions We identify a novel susceptibility locus for OA that has been previously implicated in diabetes and glycaemic traits.

@article{Li2018,
title = {MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank},
author = { Xue Li and Xiangrui Meng and Athina Spiliopoulou and Maria Timofeeva and Wei-Qi Wei and Aliya Gifford and Xia Shen and Yazhou He and Tim Varley and Paul McKeigue and Ioanna Tzoulaki and Alan F Wright and Peter Joshi and Joshua C Denny and Harry Campbell and Evropi Theodoratou},
url = {http://ard.bmj.com/content/early/2018/02/06/annrheumdis-2017-212534},
year = {2018},
date = {2018-02-06},
journal = {Annals of the Rheumatic diseases },
abstract = {Objectives We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank.

Methods We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci. We then implemented conventional Mendelian randomisation (MR) analysis to investigate the causal relevance between SUA level and disease outcomes identified from PheWAS. We next applied MR Egger analysis to detect and account for potential pleiotropy, which conventional MR analysis might mistake for causality, and used the HEIDI (heterogeneity in dependent instruments) test to remove cross-phenotype associations that were likely due to genetic linkage.

Conclusions Elevated SUA level is convincing to cause gout and inflammatory polyarthropathies, and might act as a marker for the wider range of diseases with which it associates. Our findings support further investigation on the clinical relevance of SUA level with cardiovascular, metabolic, autoimmune and respiratory diseases.},
keywords = {genetics},
pubstate = {published},
tppubtype = {article}
}

Objectives We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank.

Methods We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci. We then implemented conventional Mendelian randomisation (MR) analysis to investigate the causal relevance between SUA level and disease outcomes identified from PheWAS. We next applied MR Egger analysis to detect and account for potential pleiotropy, which conventional MR analysis might mistake for causality, and used the HEIDI (heterogeneity in dependent instruments) test to remove cross-phenotype associations that were likely due to genetic linkage.

Conclusions Elevated SUA level is convincing to cause gout and inflammatory polyarthropathies, and might act as a marker for the wider range of diseases with which it associates. Our findings support further investigation on the clinical relevance of SUA level with cardiovascular, metabolic, autoimmune and respiratory diseases.

@article{Strawbridge2017,
title = {Genome-wide analysis of self-reported risk-taking behaviour and cross-disorder genetic correlations in the UK Biobank cohor},
author = {Rona J. Strawbridge and Joey Ward and Breda Cullen and Elizabeth M. Tunbridge and Sarah Hartz and Laura Bierut and Amy Horton and Mark E. S. Bailey and Nicholas Graham and Amy Ferguson and Donald M. Lyall and Daniel Mackay and Laura M. Pidgeon and Jonathan Cavanagh and Jill P. Pell and Michael O’Donovan and Valentina Escott-Price and Paul J. Harrison and Daniel J. Smith},
url = {https://www.nature.com/articles/s41398-017-0079-1},
year = {2018},
date = {2018-02-02},
journal = {Translational Psychiatry},
abstract = {Risk-taking behaviour is a key component of several psychiatric disorders and could influence lifestyle choices such as smoking, alcohol use, and diet. As a phenotype, risk-taking behaviour therefore fits within a Research Domain Criteria (RDoC) approach, whereby identifying genetic determinants of this trait has the potential to improve our understanding across different psychiatric disorders. Here we report a genome-wide association study in 116,255 UK Biobank participants who responded yes/no to the question “Would you consider yourself a risk taker?” Risk takers (compared with controls) were more likely to be men, smokers, and have a history of psychiatric disorder. Genetic loci associated with risk-taking behaviour were identified on chromosomes 3 (rs13084531) and 6 (rs9379971). The effects of both lead SNPs were comparable between men and women. The chromosome 3 locus highlights CADM2, previously implicated in cognitive and executive functions, but the chromosome 6 locus is challenging to interpret due to the complexity of the HLA region. Risk-taking behaviour shared significant genetic risk with schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, and post-traumatic stress disorder, as well as with smoking and total obesity. Despite being based on only a single question, this study furthers our understanding of the biology of risk-taking behaviour, a trait that has a major impact on a range of common physical and mental health disorders.},
keywords = {6553, genetics, risk taking},
pubstate = {published},
tppubtype = {article}
}

Risk-taking behaviour is a key component of several psychiatric disorders and could influence lifestyle choices such as smoking, alcohol use, and diet. As a phenotype, risk-taking behaviour therefore fits within a Research Domain Criteria (RDoC) approach, whereby identifying genetic determinants of this trait has the potential to improve our understanding across different psychiatric disorders. Here we report a genome-wide association study in 116,255 UK Biobank participants who responded yes/no to the question “Would you consider yourself a risk taker?” Risk takers (compared with controls) were more likely to be men, smokers, and have a history of psychiatric disorder. Genetic loci associated with risk-taking behaviour were identified on chromosomes 3 (rs13084531) and 6 (rs9379971). The effects of both lead SNPs were comparable between men and women. The chromosome 3 locus highlights CADM2, previously implicated in cognitive and executive functions, but the chromosome 6 locus is challenging to interpret due to the complexity of the HLA region. Risk-taking behaviour shared significant genetic risk with schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, and post-traumatic stress disorder, as well as with smoking and total obesity. Despite being based on only a single question, this study furthers our understanding of the biology of risk-taking behaviour, a trait that has a major impact on a range of common physical and mental health disorders.

With an estimated one billion hypertension cases worldwide, the role of the built environment in its prevention and control is still uncertain. The present study aims to examine the associations between neighbourhood walkability and hypertension in a large and diverse population-based cohort.

MATERIALS AND METHODS:

We examined the association between neighbourhood walkability and blood pressure outcomes for N = 429,334 participants drawn from the UK Biobank and aged 38-73 years. Neighbourhood walkability was objectively modelled from detailed building footprint-level data within multi-scale functional neighbourhoods (1.0-, 1.5- and 2.0-kilometer street catchments of geocoded dwelling). A series of linear and modified Poisson regression models were employed to examine the association between walkability and outcomes of diastolic blood pressure (DBP in mmHg), systolic blood pressure (SBP in mmHg) and prevalent hypertension adjusting for socio-demographic, lifestyle and related physical environmental covariates. We also examined the relationship between walkability and change in blood pressure for a sub-sample of participants with follow-up data and tested for interaction effects of age, sex, employment status, neighbourhood SES, residential density and green exposure.

RESULTS:

Neighbourhood walkability within one-kilometer street catchment was beneficially associated with all the three blood pressure outcomes, independent of all other factors. Each interquartile increment in walkability was associated with the lower blood pressure outcomes of DBP (β = -0.358, 95% CI: -0.42, -0.29 mmHg), SBP (β = -0.833, 95% CI: -0.95, -0.72 mmHg) as well as reduced hypertension risk (RR = 0.970, 95% CI: 0.96, 0.98). The results remained consistent across spatial and temporal scales and were sensitive to sub-groups, with pronounced protective effects among female participants, those aged between 50 and 60 years, in employment, residing in deprived, high density and greener areas.

CONCLUSION:

This large population-based cohort found evidence of protective association between neighbourhood walkability and blood pressure outcomes. Given the enduring public health impact of community design on individual behaviour and lifestyle, of particular interest, are the targetted upstream-level interventions in city design aimed at optimizing walkability. Further long term studies are required to assess its sustained effects upon hypertension prevention and control.},
keywords = {11730, featured, hypertension, neighbourhood, walking},
pubstate = {published},
tppubtype = {article}
}

With an estimated one billion hypertension cases worldwide, the role of the built environment in its prevention and control is still uncertain. The present study aims to examine the associations between neighbourhood walkability and hypertension in a large and diverse population-based cohort.

MATERIALS AND METHODS:

We examined the association between neighbourhood walkability and blood pressure outcomes for N = 429,334 participants drawn from the UK Biobank and aged 38-73 years. Neighbourhood walkability was objectively modelled from detailed building footprint-level data within multi-scale functional neighbourhoods (1.0-, 1.5- and 2.0-kilometer street catchments of geocoded dwelling). A series of linear and modified Poisson regression models were employed to examine the association between walkability and outcomes of diastolic blood pressure (DBP in mmHg), systolic blood pressure (SBP in mmHg) and prevalent hypertension adjusting for socio-demographic, lifestyle and related physical environmental covariates. We also examined the relationship between walkability and change in blood pressure for a sub-sample of participants with follow-up data and tested for interaction effects of age, sex, employment status, neighbourhood SES, residential density and green exposure.

RESULTS:

Neighbourhood walkability within one-kilometer street catchment was beneficially associated with all the three blood pressure outcomes, independent of all other factors. Each interquartile increment in walkability was associated with the lower blood pressure outcomes of DBP (β = -0.358, 95% CI: -0.42, -0.29 mmHg), SBP (β = -0.833, 95% CI: -0.95, -0.72 mmHg) as well as reduced hypertension risk (RR = 0.970, 95% CI: 0.96, 0.98). The results remained consistent across spatial and temporal scales and were sensitive to sub-groups, with pronounced protective effects among female participants, those aged between 50 and 60 years, in employment, residing in deprived, high density and greener areas.

CONCLUSION:

This large population-based cohort found evidence of protective association between neighbourhood walkability and blood pressure outcomes. Given the enduring public health impact of community design on individual behaviour and lifestyle, of particular interest, are the targetted upstream-level interventions in city design aimed at optimizing walkability. Further long term studies are required to assess its sustained effects upon hypertension prevention and control.

@article{Munafò2018,
title = {Collider scope: when selection bias can substantially influence observed associations},
author = {Marcus R Munafò and Kate Tilling and Amy E Taylor and David M Evans and George Davey Smith },
url = {https://academic.oup.com/ije/article/47/1/226/4259077},
year = {2018},
date = {2018-02-01},
journal = {International Journal of Epidemiology},
abstract = {Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However, the representativeness of these samples may be limited–either through selection into studies, or by attrition from studies over time. Here we explore the potential impact of this selection bias on results obtained from these studies, from the perspective that this amounts to conditioning on a collider (i.e. a form of collider bias). Whereas it is acknowledged that selection bias will have a strong effect on representativeness and prevalence estimates, it is often assumed that it should not have a strong impact on estimates of associations. We argue that because selection can induce collider bias (which occurs when two variables independently influence a third variable, and that third variable is conditioned upon), selection can lead to substantially biased estimates of associations. In particular, selection related to phenotypes can bias associations with genetic variants associated with those phenotypes. In simulations, we show that even modest influences on selection into, or attrition from, a study can generate biased and potentially misleading estimates of both phenotypic and genotypic associations. Our results highlight the value of knowing which population your study sample is representative of. If the factors influencing selection and attrition are known, they can be adjusted for. For example, having DNA available on most participants in a birth cohort study offers the possibility of investigating the extent to which polygenic scores predict subsequent participation, which in turn would enable sensitivity analyses of the extent to which bias might distort estimates.},
keywords = {methodology},
pubstate = {published},
tppubtype = {article}
}

Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However, the representativeness of these samples may be limited–either through selection into studies, or by attrition from studies over time. Here we explore the potential impact of this selection bias on results obtained from these studies, from the perspective that this amounts to conditioning on a collider (i.e. a form of collider bias). Whereas it is acknowledged that selection bias will have a strong effect on representativeness and prevalence estimates, it is often assumed that it should not have a strong impact on estimates of associations. We argue that because selection can induce collider bias (which occurs when two variables independently influence a third variable, and that third variable is conditioned upon), selection can lead to substantially biased estimates of associations. In particular, selection related to phenotypes can bias associations with genetic variants associated with those phenotypes. In simulations, we show that even modest influences on selection into, or attrition from, a study can generate biased and potentially misleading estimates of both phenotypic and genotypic associations. Our results highlight the value of knowing which population your study sample is representative of. If the factors influencing selection and attrition are known, they can be adjusted for. For example, having DNA available on most participants in a birth cohort study offers the possibility of investigating the extent to which polygenic scores predict subsequent participation, which in turn would enable sensitivity analyses of the extent to which bias might distort estimates.

Inadequate sleep (≤ 6 and ≥ 9 h) is more prevalent in smokers than non-smokers but the extent to which sleep duration in smokers relates to smoking behaviors and cessation outcomes, is not yet clear. To begin to address this knowledge gap, we investigated the extent to which sleep duration predicted smoking behaviors and quitting intention in a population sample.
Methods

Data from current smokers who completed the baseline (N = 635) and 5-year follow-up (N = 477) assessment in the United Kingdom Biobank cohort study were analyzed. Multivariable regression models using smoking behavior outcomes (cigarettes per day, time to first cigarette, difficulty not smoking for a day, quitting intention) and sleep duration (adequate (7–8 h) versus inadequate (≤ 6 and ≥ 9 h) as the predictor were generated. All models adjusted for age, sex, race, and education.
Results

Inadequate sleep (≤ 6 and ≥ 9 h) is more prevalent in smokers than non-smokers but the extent to which sleep duration in smokers relates to smoking behaviors and cessation outcomes, is not yet clear. To begin to address this knowledge gap, we investigated the extent to which sleep duration predicted smoking behaviors and quitting intention in a population sample.
Methods

Data from current smokers who completed the baseline (N = 635) and 5-year follow-up (N = 477) assessment in the United Kingdom Biobank cohort study were analyzed. Multivariable regression models using smoking behavior outcomes (cigarettes per day, time to first cigarette, difficulty not smoking for a day, quitting intention) and sleep duration (adequate (7–8 h) versus inadequate (≤ 6 and ≥ 9 h) as the predictor were generated. All models adjusted for age, sex, race, and education.
Results

Transitioning from adequate to inadequate sleep duration may be a risk factor for developing a more “hard-core” smoking profile. The extent to which achieving healthy sleep may promote, or optimize smoking cessation treatment response, warrants investigation.

Headache is the most common neurological symptom and a leading cause of years lived with disability. We sought to identify the genetic variants associated with a broadly-defined headache phenotype in 223,773 subjects from the UK Biobank cohort.
Methods

We defined headache based on a specific question answered by the UK Biobank participants. We performed a genome-wide association study of headache as a single entity, using 74,461 cases and 149,312 controls.
Results

We identified 3343 SNPs which reached the genome-wide significance level of P < 5 × 10− 8. The SNPs were located in 28 loci, with the top SNP of rs11172113 in the LRP1 gene having a P value of 4.92 × 10− 47. Of the 28 loci, 14 have previously been associated with migraine. Among 14 new loci, rs77804065 with a P value of 5.87 × 10− 15 in the LINC02210-CRHR1 gene was the top SNP. Significant relationships between multiple brain tissues and genetic associations were identified through tissue expression analysis. We also identified significant positive genetic correlations between headache and many psychological traits.
Conclusions

Headache is the most common neurological symptom and a leading cause of years lived with disability. We sought to identify the genetic variants associated with a broadly-defined headache phenotype in 223,773 subjects from the UK Biobank cohort.
Methods

We defined headache based on a specific question answered by the UK Biobank participants. We performed a genome-wide association study of headache as a single entity, using 74,461 cases and 149,312 controls.
Results

We identified 3343 SNPs which reached the genome-wide significance level of P < 5 × 10− 8. The SNPs were located in 28 loci, with the top SNP of rs11172113 in the LRP1 gene having a P value of 4.92 × 10− 47. Of the 28 loci, 14 have previously been associated with migraine. Among 14 new loci, rs77804065 with a P value of 5.87 × 10− 15 in the LINC02210-CRHR1 gene was the top SNP. Significant relationships between multiple brain tissues and genetic associations were identified through tissue expression analysis. We also identified significant positive genetic correlations between headache and many psychological traits.
Conclusions

Our results suggest that brain function is closely related to broadly-defined headache. In addition, we found that many psychological traits have genetic correlations with headache.

Methods and analysis Prevalence estimates for monocular and binocular visual impairment were determined for the UK Biobank participants with fundus photographs and spectral domain optical coherence tomography images. Associations with socioeconomic, biometric, lifestyle and medical variables were investigated for cases with visual impairment and matched controls, using multinomial logistic regression models. Self-reported eye history and image grading results were used to identify the primary diagnoses leading to visual impairment for a sample of 25% of cases.

Results For the 65 033 UK Biobank participants, aged 40–69 years and with fundus images, 6682 (10.3%) and 1677 (2.6%) had mild visual impairment or worse in one or both eyes, respectively. Increasing deprivation, age and ethnicity were independently associated with both monocular and binocular visual impairment. No primary diagnosis for the recorded level of visual impairment could be identified for 49.8% of eyes. The most common identifiable diagnoses leading to visual impairment were cataract, amblyopia, uncorrected refractive error and vitreoretinal interface abnormalities.

Conclusions The prevalence of visual impairment in the UK Biobank study cohort is lower than for population-based studies from other industrialised countries. Monocular and binocular visual impairment are associated with increasing deprivation, age and ethnicity. The UK Biobank dataset does not allow confident identification of the causes of visual impairment, and the results may not be applicable to the wider UK population.},
keywords = {1100, binocular, monocular, visual impairment},
pubstate = {published},
tppubtype = {article}
}

Objective To determine the prevalence of, associations with and diagnoses leading to mild visual impairment or worse (logMAR >0.3) in middle-aged adults in the UK Biobank study.

Methods and analysis Prevalence estimates for monocular and binocular visual impairment were determined for the UK Biobank participants with fundus photographs and spectral domain optical coherence tomography images. Associations with socioeconomic, biometric, lifestyle and medical variables were investigated for cases with visual impairment and matched controls, using multinomial logistic regression models. Self-reported eye history and image grading results were used to identify the primary diagnoses leading to visual impairment for a sample of 25% of cases.

Results For the 65 033 UK Biobank participants, aged 40–69 years and with fundus images, 6682 (10.3%) and 1677 (2.6%) had mild visual impairment or worse in one or both eyes, respectively. Increasing deprivation, age and ethnicity were independently associated with both monocular and binocular visual impairment. No primary diagnosis for the recorded level of visual impairment could be identified for 49.8% of eyes. The most common identifiable diagnoses leading to visual impairment were cataract, amblyopia, uncorrected refractive error and vitreoretinal interface abnormalities.

Conclusions The prevalence of visual impairment in the UK Biobank study cohort is lower than for population-based studies from other industrialised countries. Monocular and binocular visual impairment are associated with increasing deprivation, age and ethnicity. The UK Biobank dataset does not allow confident identification of the causes of visual impairment, and the results may not be applicable to the wider UK population.

This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire.

METHODS:

External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries.

RESULTS:

There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals.

This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire.

METHODS:

External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries.

RESULTS:

There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals.

CONCLUSIONS:

Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.British Journal of Cancer advance online publication, 30 January 2018; doi:10.1038/bjc.2017.463 www.bjcancer.com.

Vascular aging results in stiffer arteries and may have a role in the development of cardiovascular disease (CVD). Arterial stiffness index (ASI), measured by finger photoplethysmography, and pulse pressure (PP) are 2 independent vascular aging indices. We investigated whether ASI or PP predict new-onset CVD and mortality in a large community-based population.

here is considerable discussion of the importance for increased serum 25-hydroxyvitamin D (S-25OHD) concentration associated with adequacy for bone health. Accordingly, whether long-term high S-25OHD concentration in general positively affects bone mineral density (BMD) is uncertain. We used a Mendelian randomization design to determine the association between genetically increased S-25OHD concentrations and BMD. Five single-nucleotide polymorphisms (SNPs) in or near genes encoding enzymes and carrier proteins involved in vitamin D synthesis or metabolism were used as instrumental variables to genetically predict 1 standard deviation increase in S-25OHD concentration. Summary statistics data for the associations of the S-25OHD-associated SNPs with dual-energy X-ray absorptiometry (DXA)-derived femoral neck and lumbar spine BMD were obtained from the Genetic Factors for Osteoporosis (GEFOS) Consortium (32,965 individuals) and ultrasound-derived heel estimated BMD from the UK Biobank (142,487 individuals). None of the SNPs were associated with BMD at Bonferroni-corrected significance level, but there was a suggestive association between rs6013897 near CYP24A1 and femoral neck BMD (p = 0.01). In Mendelian randomization analysis, genetically predicted 1 standard deviation increment of S-25OHD was not associated with higher femoral neck BMD (SD change in BMD 0.02; 95% confidence interval [CI] -0.03 to 0.07; p = 0.37), lumbar spine BMD (SD change in BMD 0.02; 95% CI -0.04 to 0.08; p = 0.49), or estimated BMD (g/cm2 change in BMD -0.03; 95% CI -0.05 to -0.01; p = 0.02). This study does not support a causal association between long-term elevated S-25OHD concentrations and higher BMD in generally healthy populations. These results suggest that more emphasis should be placed on the development of evidence-based cut-off points for vitamin D inadequacy rather than a general recommendation to increase S-25OHD.

Studies have suggested that women's reproductive factors are associated with the risk of cardiovascular disease (CVD); however, findings are mixed. We assessed the relationship between reproductive factors and incident CVD in the UK Biobank.

METHODS:

Between 2006 and 2010, the UK Biobank recruited over 500 000 participants aged 40-69 years across the UK. During 7 years of follow-up, 9054 incident cases of CVD (34% women), 5782 cases of coronary heart disease (CHD) (28% women), and 3489 cases of stroke (43% women) were recorded among 267 440 women and 215 088 men without a history of CVD at baseline. Cox regression models yielded adjusted hazard ratios (HRs) for CVD, CHD and stroke associated with reproductive factors.

RESULTS:

Adjusted HRs (95% CI) for CVD were 1.10 (1.01 to 1.30) for early menarche (<12 years), 0.97 (0.96 to 0.98) for each year increase in age at first birth, 1.04 (1.00 to 1.09) for each miscarriage, 1.14 (1.02 to 1.28) for each stillbirth, and 1.33 (1.19 to 1.49) for early menopause (<47 years). Hysterectomy without oophorectomy or with previous oophorectomy had adjusted HRs of 1.16 (1.06 to 1.28) and 2.30 (1.20 to 4.43) for CVD. Each additional child was associated with a HR for CVD of 1.03 (1.00 to 1.06) in women and 1.03 (1.02 to 1.05) in men.

CONCLUSIONS:

Early menarche, early menopause, earlier age at first birth, and a history of miscarriage, stillbirth or hysterectomy were each independently associated with a higher risk of CVD in later life. The relationship between the number of children and incident CVD was similar for men and women.},
keywords = {2495, cardiovascular disease, womens reproductive health},
pubstate = {published},
tppubtype = {article}
}

Studies have suggested that women's reproductive factors are associated with the risk of cardiovascular disease (CVD); however, findings are mixed. We assessed the relationship between reproductive factors and incident CVD in the UK Biobank.

METHODS:

Between 2006 and 2010, the UK Biobank recruited over 500 000 participants aged 40-69 years across the UK. During 7 years of follow-up, 9054 incident cases of CVD (34% women), 5782 cases of coronary heart disease (CHD) (28% women), and 3489 cases of stroke (43% women) were recorded among 267 440 women and 215 088 men without a history of CVD at baseline. Cox regression models yielded adjusted hazard ratios (HRs) for CVD, CHD and stroke associated with reproductive factors.

RESULTS:

Adjusted HRs (95% CI) for CVD were 1.10 (1.01 to 1.30) for early menarche (<12 years), 0.97 (0.96 to 0.98) for each year increase in age at first birth, 1.04 (1.00 to 1.09) for each miscarriage, 1.14 (1.02 to 1.28) for each stillbirth, and 1.33 (1.19 to 1.49) for early menopause (<47 years). Hysterectomy without oophorectomy or with previous oophorectomy had adjusted HRs of 1.16 (1.06 to 1.28) and 2.30 (1.20 to 4.43) for CVD. Each additional child was associated with a HR for CVD of 1.03 (1.00 to 1.06) in women and 1.03 (1.02 to 1.05) in men.

CONCLUSIONS:

Early menarche, early menopause, earlier age at first birth, and a history of miscarriage, stillbirth or hysterectomy were each independently associated with a higher risk of CVD in later life. The relationship between the number of children and incident CVD was similar for men and women.

Multimorbidity is common in COPD and associated with high levels of polypharmacy. Co-prescription of drugs with various ADRs is common. Future research should examine the effects on healthcare outcomes of co-prescribing multiple drugs with similar potential ADRs. Clinical guidelines should emphasise assessment of multimorbidity and ADR risk.},
keywords = {14151, COPD, multimorbidity},
pubstate = {published},
tppubtype = {article}
}

This study aims: (1) to describe the pattern and extent of multimorbidity and polypharmacy in UK Biobank participants with chronic obstructive pulmonary disease (COPD) and (2) to identify which comorbidities are associated with increased risk of adverse drug reactions (ADRs) resulting from polypharmacy.

Multimorbidity is common in COPD and associated with high levels of polypharmacy. Co-prescription of drugs with various ADRs is common. Future research should examine the effects on healthcare outcomes of co-prescribing multiple drugs with similar potential ADRs. Clinical guidelines should emphasise assessment of multimorbidity and ADR risk.

@article{Hall2018,
title = {Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank.},
author = {LS Hall and MJ Adams and A Arnau-Soler and TK Clarke and DM Howard and Y Zeng and G Davies and SP Hagenaars and A Maria Fernandez-Pujals and J Gibson and EM Wigmore and TS Boutin and C Hayward and DJ Porteous and IJ Deary and PA Thomson and CS Haley and AM McIntosh},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29317602},
year = {2018},
date = {2018-01-10},
journal = {Translational Psychiatry},
abstract = {Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.},
keywords = {4844, depression, generation scotland, genetics},
pubstate = {published},
tppubtype = {article}
}

Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.

Using UK Biobank data, this study sought to explain the causal relationship between alcohol intake and cognitive decline in middle and older aged populations.

Methods:

Data from 13 342 men and women, aged between 40 and 73 years were used in regression analysis that tested the functional relationship and impact of alcohol on cognitive performance. Performance was measured using mean reaction time (RT) and intra-individual variation (IIV) in RT, collected in response to a perceptual matching task. Covariates included body mass index, physical activity, tobacco use, socioeconomic status, education and baseline cognitive function.

The relationship between alcohol use and cognitive function is non-linear. Consuming more than one UK standard unit of alcohol per day is detrimental to cognitive performance and is more pronounced in older populations.},
keywords = {15697, alcohol, cognition},
pubstate = {published},
tppubtype = {article}
}

Using UK Biobank data, this study sought to explain the causal relationship between alcohol intake and cognitive decline in middle and older aged populations.

Methods:

Data from 13 342 men and women, aged between 40 and 73 years were used in regression analysis that tested the functional relationship and impact of alcohol on cognitive performance. Performance was measured using mean reaction time (RT) and intra-individual variation (IIV) in RT, collected in response to a perceptual matching task. Covariates included body mass index, physical activity, tobacco use, socioeconomic status, education and baseline cognitive function.

The relationship between alcohol use and cognitive function is non-linear. Consuming more than one UK standard unit of alcohol per day is detrimental to cognitive performance and is more pronounced in older populations.

We investigated associations between calcium/vitamin D supplementation and incident cardiovascular events/deaths in a UK population-based cohort. UK Biobank is a large prospective cohort comprising 502,637 men and women aged 40-69 years at recruitment. Supplementation with calcium/vitamin D was self-reported, and information on incident hospital admission (ICD-10) for ischaemic heart disease (IHD), myocardial infarction (MI) any cardiovascular event, and subsequent death, was obtained from linkage to national registers. Cox Proportional Hazards models were used to investigate longitudinal relationships between calcium/vitamin D supplementation and hospital admission for men/women, controlling for covariates. 475,255 participants (median age 58years, 55.8% women) had complete data on calcium/vitamin D supplementation. 33,437 participants reported taking calcium supplements; 19,089 vitamin D; 10,007 both. In crude and adjusted analyses, there were no associations between use of calcium supplements and risk of incident hospital admission with either IHD, MI or any cardiovascular event, or subsequent death. Thus, for example, in unadjusted models, the hazard ratio (HR) for admission with myocardial infarction was 0.97 (95%CI:0.79,1.20; p = 0.79) amongst women taking calcium supplementation. Corresponding HR for men: 1.16 (95%CI:0.92,1.46;p = 0.22). After full adjustment, HR(95%CI) were 0.82 (0.62,1.07), p = 0.14 amongst women and 1.12 (0.85,1.48), p = 0.41 amongst men. Adjusted HR(95%CI) for admission with IHD were 1.05 (0.92,1.19), p = 0.50 amongst women and 0.97 (0.82,1.15), p = 0.77 amongst men. Results were similar for any cardiovascular admission and for vitamin D and combination supplementation. There were no associations with death, and in women, further adjustment for HRT use did not alter the associations. In this very large prospective cohort, there was no evidence that use of calcium/vitamin D supplementation was associated with increased risk of hospital admission or death following ischaemic or non-ischaemic cardiovascular events.

The present study tested the hypothesis that arterial stiffness will be elevated across overall and specific inflammatory disorders compared with an inflammation-free comparison group.

METHODS:

Adults (n=171 125) aged 40-70 years from the UK Biobank who were cardiovascular disease (CVD) free and who had their arterial stiffness assessed at the time of study recruitment between 2006 and 2010 were included. The main exposure was represented by a global measure of chronic inflammatory disorders. Two inflammatory biomarker measures (eg, leucocytes count, granulocytes count) were included as markers of inflammation severity. The arterial stiffness index assessed by a non-invasive technique represented the study primary outcome measure.

RESULTS:

A total of 5976 (3%) participants diagnosed with inflammatory disorders and 165 149 participants without an inflammatory disorder had data on arterial stiffness. Adjusted linear regression analyses revealed a 14% increment in mean arterial stiffness for chronic inflammatory disorders (beta coefficient (β) 1.14, 95% CI 1.05 to 1.24, P=0.002) compared with no chronic inflammatory disorder. Arterial stiffness tended to increase (P value=0.031) with tertiles of leucocytes and granulocytes count. For instance, mean arterial stiffness values increased from 1.11 (95% CI 0.96 to 1.29) in the first tertile to 1.17 (95% CI 1.02 to 1.34) in the second tertile, and 1.21 (95% CI 1.05 to 1.39) in the third tertile of leucocytes count. There was evidence for similar associations with some of the most common individual inflammatory disorders, including psoriasis and rheumatoid arthritis.

The present study tested the hypothesis that arterial stiffness will be elevated across overall and specific inflammatory disorders compared with an inflammation-free comparison group.

METHODS:

Adults (n=171 125) aged 40-70 years from the UK Biobank who were cardiovascular disease (CVD) free and who had their arterial stiffness assessed at the time of study recruitment between 2006 and 2010 were included. The main exposure was represented by a global measure of chronic inflammatory disorders. Two inflammatory biomarker measures (eg, leucocytes count, granulocytes count) were included as markers of inflammation severity. The arterial stiffness index assessed by a non-invasive technique represented the study primary outcome measure.

RESULTS:

A total of 5976 (3%) participants diagnosed with inflammatory disorders and 165 149 participants without an inflammatory disorder had data on arterial stiffness. Adjusted linear regression analyses revealed a 14% increment in mean arterial stiffness for chronic inflammatory disorders (beta coefficient (β) 1.14, 95% CI 1.05 to 1.24, P=0.002) compared with no chronic inflammatory disorder. Arterial stiffness tended to increase (P value=0.031) with tertiles of leucocytes and granulocytes count. For instance, mean arterial stiffness values increased from 1.11 (95% CI 0.96 to 1.29) in the first tertile to 1.17 (95% CI 1.02 to 1.34) in the second tertile, and 1.21 (95% CI 1.05 to 1.39) in the third tertile of leucocytes count. There was evidence for similar associations with some of the most common individual inflammatory disorders, including psoriasis and rheumatoid arthritis.

CONCLUSION:

Arterial stiffness was associated with multiple chronic inflammatory disorders. An increasing trend in mean arterial stiffness was also documented with increasing tertiles of different inflammatory biomarkers. Future studies are needed to investigate the discriminant value of arterial stiffness to predict major CVD events within various inflammatory disorders.

A fundamental precept of the carbohydrate-insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight.
METHODS:

Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI.
RESULTS:

Higher genetically determined insulin-30 was strongly associated with higher BMI (β = 0.098, P = 2.2 × 10-21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30.
CONCLUSIONS:

A fundamental precept of the carbohydrate-insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight.
METHODS:

Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI.
RESULTS:

Higher genetically determined insulin-30 was strongly associated with higher BMI (β = 0.098, P = 2.2 × 10-21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30.
CONCLUSIONS:

Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate-insulin model of obesity.

Atrial fibrillation (AF) is a common cardiac arrhythmia and a major risk factor for stroke, heart failure, and premature death. The pathogenesis of AF remains poorly understood, which contributes to the current lack of highly effective treatments. To understand the genetic variation and biology underlying AF, we undertook a genome-wide association study (GWAS) of 6,337 AF individuals and 61,607 AF-free individuals from Norway, including replication in an additional 30,679 AF individuals and 278,895 AF-free individuals. Through genotyping and dense imputation mapping from whole-genome sequencing, we tested almost nine million genetic variants across the genome and identified seven risk loci, including two novel loci. One novel locus (lead single-nucleotide variant [SNV] rs12614435; p = 6.76 × 10−18) comprised intronic and several highly correlated missense variants situated in the I-, A-, and M-bands of titin, which is the largest protein in humans and responsible for the passive elasticity of heart and skeletal muscle. The other novel locus (lead SNV rs56202902; p = 1.54 × 10−11) covered a large, gene-dense chromosome 1 region that has previously been linked to cardiac conduction. Pathway and functional enrichment analyses suggested that many AF-associated genetic variants act through a mechanism of impaired muscle cell differentiation and tissue formation during fetal heart development.

@article{Ktena2017,
title = {Metric learning with spectral graph convolutions on brain connectivity networks},
author = { Sofia Ira Ktena and Sarah Parisot and Enzo Ferrante and Martin Rajchla and Matthew Lee and Ben Glocker and Daniel Rueckert},
url = {https://www.sciencedirect.com/science/article/pii/S1053811917310765},
year = {2017},
date = {2017-12-24},
journal = {NeuroImage},
abstract = {Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition problems. In the field of neuroscience, where such representations are commonly used to model structural or functional connectivity between a set of brain regions, graphs have proven to be of great importance. This is mainly due to the capability of revealing patterns related to brain development and disease, which were previously unknown. Evaluating similarity between these brain connectivity networks in a manner that accounts for the graph structure and is tailored for a particular application is, however, non-trivial. Most existing methods fail to accommodate the graph structure, discarding information that could be beneficial for further classification or regression analyses based on these similarities. We propose to learn a graph similarity metric using a siamese graph convolutional neural network (s-GCN) in a supervised setting. The proposed framework takes into consideration the graph structure for the evaluation of similarity between a pair of graphs, by employing spectral graph convolutions that allow the generalisation of traditional convolutions to irregular graphs and operates in the graph spectral domain. We apply the proposed model on two datasets: the challenging ABIDE database, which comprises functional MRI data of 403 patients with autism spectrum disorder (ASD) and 468 healthy controls aggregated from multiple acquisition sites, and a set of 2500 subjects from UK Biobank. We demonstrate the performance of the method for the tasks of classification between matching and non-matching graphs, as well as individual subject classification and manifold learning, showing that it leads to significantly improved results compared to traditional methods.},
keywords = {12579, brain, graphs, imaging, methodology},
pubstate = {published},
tppubtype = {article}
}

Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition problems. In the field of neuroscience, where such representations are commonly used to model structural or functional connectivity between a set of brain regions, graphs have proven to be of great importance. This is mainly due to the capability of revealing patterns related to brain development and disease, which were previously unknown. Evaluating similarity between these brain connectivity networks in a manner that accounts for the graph structure and is tailored for a particular application is, however, non-trivial. Most existing methods fail to accommodate the graph structure, discarding information that could be beneficial for further classification or regression analyses based on these similarities. We propose to learn a graph similarity metric using a siamese graph convolutional neural network (s-GCN) in a supervised setting. The proposed framework takes into consideration the graph structure for the evaluation of similarity between a pair of graphs, by employing spectral graph convolutions that allow the generalisation of traditional convolutions to irregular graphs and operates in the graph spectral domain. We apply the proposed model on two datasets: the challenging ABIDE database, which comprises functional MRI data of 403 patients with autism spectrum disorder (ASD) and 468 healthy controls aggregated from multiple acquisition sites, and a set of 2500 subjects from UK Biobank. We demonstrate the performance of the method for the tasks of classification between matching and non-matching graphs, as well as individual subject classification and manifold learning, showing that it leads to significantly improved results compared to traditional methods.

Red and processed meat may be risk factors for breast cancer due to their iron content, administration of oestrogens to cattle or mutagens created during cooking. We studied the associations in UK Biobank and then included the results in a meta-analysis of published cohort studies.

Methods

UK Biobank, a general population cohort study, recruited participants aged 40–69 years. Incident breast cancer was ascertained via linkage to routine hospital admission, cancer registry and death certificate data. Univariate and multivariable Cox proportional hazard models were used to explore the associations between red and processed meat consumption and breast cancer. Previously published cohort studies were identified from a systematic review using PubMed and Ovid and a meta-analysis conducted using a random effects model.

Red and processed meat may be risk factors for breast cancer due to their iron content, administration of oestrogens to cattle or mutagens created during cooking. We studied the associations in UK Biobank and then included the results in a meta-analysis of published cohort studies.

Methods

UK Biobank, a general population cohort study, recruited participants aged 40–69 years. Incident breast cancer was ascertained via linkage to routine hospital admission, cancer registry and death certificate data. Univariate and multivariable Cox proportional hazard models were used to explore the associations between red and processed meat consumption and breast cancer. Previously published cohort studies were identified from a systematic review using PubMed and Ovid and a meta-analysis conducted using a random effects model.

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.
},
keywords = {12505, complex traits, natural selection},
pubstate = {published},
tppubtype = {article}
}

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.

@article{Vicente2017,
title = {Lessons from ten years of genome-wide association studies of asthma},
author = {Cristina T Vicente and Joana A Revez and Manuel A R Ferreira},
url = {http://onlinelibrary.wiley.com/doi/10.1038/cti.2017.54/abstract},
year = {2017},
date = {2017-12-15},
journal = {Clinical and Translational Immunology},
abstract = {Twenty-five genome-wide association studies (GWAS) of asthma were published between 2007 and 2016, the largest with a sample size of 157242 individuals. Across these studies, 39 genetic variants in low linkage disequilibrium (LD) with each other were reported to associate with disease risk at a significance threshold of P<5 × 10−8, including 31 in populations of European ancestry. Results from analyses of the UK Biobank data (n=380 503) indicate that at least 28 of the 31 associations reported in Europeans represent true-positive findings, collectively explaining 2.5% of the variation in disease liability (median of 0.06% per variant). We identified 49 transcripts as likely target genes of the published asthma risk variants, mostly based on LD with expression quantitative trait loci (eQTL). Of these genes, 16 were previously implicated in disease pathophysiology by functional studies, including TSLP, TNFSF4, ADORA1, CHIT1 and USF1. In contrast, at present, there is limited or no functional evidence directly implicating the remaining 33 likely target genes in asthma pathophysiology. Some of these genes have a known function that is relevant to allergic disease, including F11R, CD247, PGAP3, AAGAB, CAMK4 and PEX14, and so could be prioritized for functional follow-up. We conclude by highlighting three areas of research that are essential to help translate GWAS findings into clinical research or practice, namely validation of target gene predictions, understanding target gene function and their role in disease pathophysiology and genomics-guided prioritization of targets for drug development.},
keywords = {asthma, genetics},
pubstate = {published},
tppubtype = {article}
}

Twenty-five genome-wide association studies (GWAS) of asthma were published between 2007 and 2016, the largest with a sample size of 157242 individuals. Across these studies, 39 genetic variants in low linkage disequilibrium (LD) with each other were reported to associate with disease risk at a significance threshold of P<5 × 10−8, including 31 in populations of European ancestry. Results from analyses of the UK Biobank data (n=380 503) indicate that at least 28 of the 31 associations reported in Europeans represent true-positive findings, collectively explaining 2.5% of the variation in disease liability (median of 0.06% per variant). We identified 49 transcripts as likely target genes of the published asthma risk variants, mostly based on LD with expression quantitative trait loci (eQTL). Of these genes, 16 were previously implicated in disease pathophysiology by functional studies, including TSLP, TNFSF4, ADORA1, CHIT1 and USF1. In contrast, at present, there is limited or no functional evidence directly implicating the remaining 33 likely target genes in asthma pathophysiology. Some of these genes have a known function that is relevant to allergic disease, including F11R, CD247, PGAP3, AAGAB, CAMK4 and PEX14, and so could be prioritized for functional follow-up. We conclude by highlighting three areas of research that are essential to help translate GWAS findings into clinical research or practice, namely validation of target gene predictions, understanding target gene function and their role in disease pathophysiology and genomics-guided prioritization of targets for drug development.

Polygenic risk scores for ADHD derived from the mega genome-wide association study (20,183 cases and 35,191 control subjects) were computed in a large-scale adult population sample (N = 135,726) recruited by the UK Biobank. Regression analyses were conducted to investigate whether polygenic risk for ADHD is associated with related traits and disorders in this population sample. The effects of sex were investigated via inclusion of an interaction term in the models.
Results

Our findings suggest that common genetic variation underlying risk for clinically diagnosed ADHD also contributes to higher body mass index, neuroticism, anxiety and depressive disorders, alcohol and nicotine use, risk taking, and lower general cognitive ability in the general population. These findings suggest that the co-occurrence of several traits with ADHD is partly explained by the same common genetic variants.},
keywords = {genetics},
pubstate = {published},
tppubtype = {article}
}

A recent large-scale mega genome-wide association study identified, for the first time, genetic variants at 12 loci significantly associated with attention-deficit/hyperactivity disorder (ADHD). In this study we use a powerful polygenic approach, with polygenic scores derived from the genome-wide association study, to investigate the etiological overlap between ADHD and frequently co-occurring traits and disorders.
Methods

Polygenic risk scores for ADHD derived from the mega genome-wide association study (20,183 cases and 35,191 control subjects) were computed in a large-scale adult population sample (N = 135,726) recruited by the UK Biobank. Regression analyses were conducted to investigate whether polygenic risk for ADHD is associated with related traits and disorders in this population sample. The effects of sex were investigated via inclusion of an interaction term in the models.
Results

Our findings suggest that common genetic variation underlying risk for clinically diagnosed ADHD also contributes to higher body mass index, neuroticism, anxiety and depressive disorders, alcohol and nicotine use, risk taking, and lower general cognitive ability in the general population. These findings suggest that the co-occurrence of several traits with ADHD is partly explained by the same common genetic variants.

Low-carbohydrate diets are becoming increasingly popular, although their dietary quality outside of clinical studies is unknown. A previous study analysed the dietary intake in people consuming a reduced-carbohydrate diet (<40% calories). However, it is not clear what foods people consume when carbohydrate is reduced to below 26% of total calories.
METHODS:

Low-carbohydrate diets are becoming increasingly popular, although their dietary quality outside of clinical studies is unknown. A previous study analysed the dietary intake in people consuming a reduced-carbohydrate diet (<40% calories). However, it is not clear what foods people consume when carbohydrate is reduced to below 26% of total calories.
METHODS:

The built environment might be associated with development of obesity and related disorders. We examined whether neighbourhood exposure to fast-food outlets and physical activity facilities were associated with adiposity in UK adults.

Methods

We used cross-sectional observational data from UK Biobank. Participants were aged 40–70 years and attended 21 assessment centres between 2006 and 2010. Using linked data on environments around each participant's residential address, we examined whether density of physical activity facilities and proximity to fast-food outlets were associated with waist circumference, body-mass index (BMI), and body fat percentage. We used multilevel linear regression models adjusted for potential confounders, and conducted several sensitivity analyses.

Findings

Complete case sample sizes were 401 917 (waist circumference models), 401 435 (BMI), and 395 640 (body fat percentage). Greater density of physical activity facilities within 1000 m of home was independently associated with smaller waist circumference and lower BMI and body fat percentage. Compared with people with no nearby facilities, those with at least six facilities close to home had 1·22 cm smaller waist circumference (95% CI −1·64 to −0·80), 0·57 kg/m2 lower BMI (−0·74 to −0·39), and 0·81 percentage points lower body fat (−1·03 to −0·59). Living further from a fast-food outlet was weakly associated with waist circumference and BMI, mostly among women. Compared with people living fewer than 500 m from a fast-food outlet, those living at least 2000 m away had 0·26 cm smaller waist circumference (−0·52 to 0·01).

Interpretation

This study shows strong associations between high densities of physical activity facilities and lower adiposity for adults in mid-life. We observed weaker associations for access to fast food, but these are likely to be underestimated owing to limitations of the food environment measure. Policy makers should consider interventions aimed at tackling the obesogenic built environment.

The built environment might be associated with development of obesity and related disorders. We examined whether neighbourhood exposure to fast-food outlets and physical activity facilities were associated with adiposity in UK adults.

Methods

We used cross-sectional observational data from UK Biobank. Participants were aged 40–70 years and attended 21 assessment centres between 2006 and 2010. Using linked data on environments around each participant's residential address, we examined whether density of physical activity facilities and proximity to fast-food outlets were associated with waist circumference, body-mass index (BMI), and body fat percentage. We used multilevel linear regression models adjusted for potential confounders, and conducted several sensitivity analyses.

Findings

Complete case sample sizes were 401 917 (waist circumference models), 401 435 (BMI), and 395 640 (body fat percentage). Greater density of physical activity facilities within 1000 m of home was independently associated with smaller waist circumference and lower BMI and body fat percentage. Compared with people with no nearby facilities, those with at least six facilities close to home had 1·22 cm smaller waist circumference (95% CI −1·64 to −0·80), 0·57 kg/m2 lower BMI (−0·74 to −0·39), and 0·81 percentage points lower body fat (−1·03 to −0·59). Living further from a fast-food outlet was weakly associated with waist circumference and BMI, mostly among women. Compared with people living fewer than 500 m from a fast-food outlet, those living at least 2000 m away had 0·26 cm smaller waist circumference (−0·52 to 0·01).

Interpretation

This study shows strong associations between high densities of physical activity facilities and lower adiposity for adults in mid-life. We observed weaker associations for access to fast food, but these are likely to be underestimated owing to limitations of the food environment measure. Policy makers should consider interventions aimed at tackling the obesogenic built environment.

Previous reports have implicated multiple genetic loci associated with AF, but the contributions of genome-wide variation to AF susceptibility have not been quantified.
METHODS AND RESULTS:

We assessed the contribution of genome-wide single-nucleotide polymorphism variation to AF risk (single-nucleotide polymorphism heritability, h2g ) using data from 120 286 unrelated individuals of European ancestry (2987 with AF) in the population-based UK Biobank. We ascertained AF based on self-report, medical record billing codes, procedure codes, and death records. We estimated h2g using a variance components method with variants having a minor allele frequency ≥1%. We evaluated h2g in age, sex, and genomic strata of interest. The h2g for AF was 22.1% (95% confidence interval, 15.6%-28.5%) and was similar for early- versus older-onset AF (≤65 versus >65 years of age), as well as for men and women. The proportion of AF variance explained by genetic variation was mainly accounted for by common (minor allele frequency, ≥5%) variants (20.4%; 95% confidence interval, 15.1%-25.6%). Only 6.4% (95% confidence interval, 5.1%-7.7%) of AF variance was attributed to variation within known AF susceptibility, cardiac arrhythmia, and cardiomyopathy gene regions.
CONCLUSIONS:

Genetic variation contributes substantially to AF risk. The risk for AF conferred by genomic variation is similar to that observed for several other cardiovascular diseases. Established AF loci only explain a moderate proportion of disease risk, suggesting that furt},
keywords = {17488, atrial fibrillation, genetics},
pubstate = {published},
tppubtype = {article}
}

Previous reports have implicated multiple genetic loci associated with AF, but the contributions of genome-wide variation to AF susceptibility have not been quantified.
METHODS AND RESULTS:

We assessed the contribution of genome-wide single-nucleotide polymorphism variation to AF risk (single-nucleotide polymorphism heritability, h2g ) using data from 120 286 unrelated individuals of European ancestry (2987 with AF) in the population-based UK Biobank. We ascertained AF based on self-report, medical record billing codes, procedure codes, and death records. We estimated h2g using a variance components method with variants having a minor allele frequency ≥1%. We evaluated h2g in age, sex, and genomic strata of interest. The h2g for AF was 22.1% (95% confidence interval, 15.6%-28.5%) and was similar for early- versus older-onset AF (≤65 versus >65 years of age), as well as for men and women. The proportion of AF variance explained by genetic variation was mainly accounted for by common (minor allele frequency, ≥5%) variants (20.4%; 95% confidence interval, 15.1%-25.6%). Only 6.4% (95% confidence interval, 5.1%-7.7%) of AF variance was attributed to variation within known AF susceptibility, cardiac arrhythmia, and cardiomyopathy gene regions.
CONCLUSIONS:

Genetic variation contributes substantially to AF risk. The risk for AF conferred by genomic variation is similar to that observed for several other cardiovascular diseases. Established AF loci only explain a moderate proportion of disease risk, suggesting that furt

Obesity is a major health issue and an important public health target for urban design. However, the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. We examined the association of obesity with residential density in a large and diverse population sample drawn from the UK Biobank to identify healthy-weight-sustaining density environments.
Methods

For this full-data, cross-sectional analysis, we used UK Biobank data for adult men and women aged 37–73 years from 22 cities across the UK. Baseline examinations were done between 2006 and 2010. Residential unit density was objectively assessed within a 1 km street catchment of a participant's residence. Other activity-influencing built environment factors were measured in terms of density of retail, public transport, and street-level movement density, which were modelled from network analyses of through movement of street links within the defined catchment. We regressed adiposity indicators of body-mass index (BMI; kg/m2), waist circumference (cm), whole body fat (kg), and obesity (WHO criteria of BMI ≥30 kg/m2) on residential density (units per km2), adjusting for activity-influencing built environment factors and individual covariates. We also investigated effect modification by age, sex, employment status, and physical activity. We used a series of linear continuous and logistic regression models and non-linear restricted cubic spline models as appropriate.
Findings

Of 502 649 adults in the prospective cohort, 419 562 (83·5%) participants across 22 UK Biobank assessment centres met baseline data requirements and were included in the analytic sample. The fitted restricted cubic spline adiposity-residential density dose–response curve identified a turning point at a residential density of 1800 residential units per km2. Below a residential density of 1800 units per km2, an increment of 1000 units per km2 was positively related with adiposity, being associated with higher BMI (β 0·19 kg/m2, 95% CI 0·14 to 0·24), waist circumference (β 0·41 cm, 0·28 to 0·54), and whole body fat (β 0·40 kg, 0·30 to 0·50), and with increased odds of obesity (odds ratio [OR] 1·10, 1·07 to 1·14). Beyond 1800 units per km2, residential density had a protective effect on adiposity and was associated with lower BMI (β −0·22 kg/m2, −0·25 to −0·20), waist circumference (β −0·54 cm, −0·61 to −0·48), and whole body fat (β −0·38 kg, −0·43 to −0·33), and with decreased odds of obesity (OR 0·91, 0·90 to 0·93). Subgroup analyses identified more pronounced protective effects of residential density among individuals who were younger, female, in employment, and accumulating higher levels of physical activity, except in the case of whole body fat, for which the protective effects were stronger in men.
Interpretation

Housing-level policy related to the optimisation of healthy density in cities might be a potential upstream-level public health intervention towards the minimisation and offsetting of obesity; however, further research based on accumulated prospective data is necessary for evidencing specific pathways. The findings might mean that governments, such as the UK Government, who are attempting to prevent suburban densification by, for example, prohibiting the subdivision of single lot housing and the conversion of domestic gardens to housing lots, will potentially have the effect of inhibiting the conversion of suburbs into more healthy places to live.
Funding

Obesity is a major health issue and an important public health target for urban design. However, the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. We examined the association of obesity with residential density in a large and diverse population sample drawn from the UK Biobank to identify healthy-weight-sustaining density environments.
Methods

For this full-data, cross-sectional analysis, we used UK Biobank data for adult men and women aged 37–73 years from 22 cities across the UK. Baseline examinations were done between 2006 and 2010. Residential unit density was objectively assessed within a 1 km street catchment of a participant's residence. Other activity-influencing built environment factors were measured in terms of density of retail, public transport, and street-level movement density, which were modelled from network analyses of through movement of street links within the defined catchment. We regressed adiposity indicators of body-mass index (BMI; kg/m2), waist circumference (cm), whole body fat (kg), and obesity (WHO criteria of BMI ≥30 kg/m2) on residential density (units per km2), adjusting for activity-influencing built environment factors and individual covariates. We also investigated effect modification by age, sex, employment status, and physical activity. We used a series of linear continuous and logistic regression models and non-linear restricted cubic spline models as appropriate.
Findings

Of 502 649 adults in the prospective cohort, 419 562 (83·5%) participants across 22 UK Biobank assessment centres met baseline data requirements and were included in the analytic sample. The fitted restricted cubic spline adiposity-residential density dose–response curve identified a turning point at a residential density of 1800 residential units per km2. Below a residential density of 1800 units per km2, an increment of 1000 units per km2 was positively related with adiposity, being associated with higher BMI (β 0·19 kg/m2, 95% CI 0·14 to 0·24), waist circumference (β 0·41 cm, 0·28 to 0·54), and whole body fat (β 0·40 kg, 0·30 to 0·50), and with increased odds of obesity (odds ratio [OR] 1·10, 1·07 to 1·14). Beyond 1800 units per km2, residential density had a protective effect on adiposity and was associated with lower BMI (β −0·22 kg/m2, −0·25 to −0·20), waist circumference (β −0·54 cm, −0·61 to −0·48), and whole body fat (β −0·38 kg, −0·43 to −0·33), and with decreased odds of obesity (OR 0·91, 0·90 to 0·93). Subgroup analyses identified more pronounced protective effects of residential density among individuals who were younger, female, in employment, and accumulating higher levels of physical activity, except in the case of whole body fat, for which the protective effects were stronger in men.
Interpretation

Housing-level policy related to the optimisation of healthy density in cities might be a potential upstream-level public health intervention towards the minimisation and offsetting of obesity; however, further research based on accumulated prospective data is necessary for evidencing specific pathways. The findings might mean that governments, such as the UK Government, who are attempting to prevent suburban densification by, for example, prohibiting the subdivision of single lot housing and the conversion of domestic gardens to housing lots, will potentially have the effect of inhibiting the conversion of suburbs into more healthy places to live.
Funding

University of Hong Kong, UK Biobank, and UK Economic & Social Research Council.

Objective: To expand the number of genome-wide significant loci, catalog functional insights, and enhance our understanding of the genetic architecture of CAD.

Methods and Results: We performed a genome-wide association study (GWAS) in 34,541 CAD cases and 261,984 controls of UK biobank Resource followed by replication in 88,192 cases and 162,544 controls from CARDIoGRAMplusC4D. We identified 75 loci that replicated and were genome-wide significant (P<5x10-8) in meta-analysis, 13 of which had not been reported previously. Next, to further identify novel loci we identified all promising (P<0.0001) loci in the CARDIoGRAMplusC4D data and performed reciprocal replication and meta-analyses with UK biobank. This led to the identification of 21 additional novel loci reaching genome-wide significance (P<5x10-8) in meta-analysis. Finally, we performed a genome wide meta-analysis of all available data revealing 30 additional novel loci (P<5x10-8) without further replication. The increase in sample size by UK Biobank raised the number of reconstituted gene-sets from 4.2% to 13.9% of all gene-sets to be involved in CAD. For the 64 novel loci, 155 candidate causal genes were prioritized, many without an obvious connection to CAD. Fine-mapping of the 161 CAD loci generated lists of credible sets of single causal variants and genes for functional follow-up. Genetic risk variants of CAD were linked to development of atrial fibrillation, heart failure and death.

Conclusions: We identified 64 novel genetic risk loci for CAD and performed fine-mapping of all 161 risk loci to obtain a credible set of causal variants. The large expansion of reconstituted gene-sets argues in favor of an expanded "omnigenic model" view on the genetic architecture of CAD. },
keywords = {12006, featured, genetics, heart disease},
pubstate = {published},
tppubtype = {article}
}

Rationale: Coronary artery disease (CAD) is a complex phenotype driven by genetic and environmental factors. 97 genetic risk loci have been identified so far, but the identification of additional susceptibility loci might be important to enhance our understanding of the genetic architecture of CAD.

Objective: To expand the number of genome-wide significant loci, catalog functional insights, and enhance our understanding of the genetic architecture of CAD.

Methods and Results: We performed a genome-wide association study (GWAS) in 34,541 CAD cases and 261,984 controls of UK biobank Resource followed by replication in 88,192 cases and 162,544 controls from CARDIoGRAMplusC4D. We identified 75 loci that replicated and were genome-wide significant (P<5x10-8) in meta-analysis, 13 of which had not been reported previously. Next, to further identify novel loci we identified all promising (P<0.0001) loci in the CARDIoGRAMplusC4D data and performed reciprocal replication and meta-analyses with UK biobank. This led to the identification of 21 additional novel loci reaching genome-wide significance (P<5x10-8) in meta-analysis. Finally, we performed a genome wide meta-analysis of all available data revealing 30 additional novel loci (P<5x10-8) without further replication. The increase in sample size by UK Biobank raised the number of reconstituted gene-sets from 4.2% to 13.9% of all gene-sets to be involved in CAD. For the 64 novel loci, 155 candidate causal genes were prioritized, many without an obvious connection to CAD. Fine-mapping of the 161 CAD loci generated lists of credible sets of single causal variants and genes for functional follow-up. Genetic risk variants of CAD were linked to development of atrial fibrillation, heart failure and death.

Conclusions: We identified 64 novel genetic risk loci for CAD and performed fine-mapping of all 161 risk loci to obtain a credible set of causal variants. The large expansion of reconstituted gene-sets argues in favor of an expanded "omnigenic model" view on the genetic architecture of CAD.

We undertook a genome-wide association study (GWAS) of parental longevity in European descent UK Biobank participants. For combined mothers' and fathers' attained age, 10 loci were associated (p<5*10-8), including 8 previously identified for traits including survival, Alzheimer’s and cardiovascular disease. Of these, 4 were also associated with longest 10% survival (mothers age ≥90 years, fathers ≥87 years), with 2 additional associations including MC2R intronic variants (coding for the adrenocorticotropic hormone receptor). Mother’s age at death was associated with 3 additional loci (2 linked to autoimmune conditions), and 8 for fathers only. An attained age genetic risk score associated with parental survival in the US Health and Retirement Study and the Wisconsin Longitudinal Study and with having a centenarian parent (n=1,181) in UK Biobank. The results suggest that human longevity is highly polygenic with prominent roles for loci likely involved in cellular senescence and inflammation, plus lipid metabolism and cardiovascular conditions. There may also be gender specific routes to longevity.

There has been a significant increase in the prescribing of medication for chronic non-cancer pain. In a UK population sample, we aimed to assess cardio-metabolic (CM) health in those taking these chronic pain medications.

METHODS:

133,401 participants from the UK Biobank cohort were studied. BMI, waist cm and hypertension were compared between those on drugs prescribed for chronic pain and CM drugs to those on CM drugs only. Multiple confounders were controlled for.

The impact of medications for chronic pain and sleep upon CM health and obesity is of concern for these classes of drugs which have been recently labelled as dependency forming medications. The results from this cross sectional study warrants further investigation and adds further support to calls for these medications to be prescribed for shorter periods.},
keywords = {analgesic drugs, drugs},
pubstate = {published},
tppubtype = {article}
}

There has been a significant increase in the prescribing of medication for chronic non-cancer pain. In a UK population sample, we aimed to assess cardio-metabolic (CM) health in those taking these chronic pain medications.

METHODS:

133,401 participants from the UK Biobank cohort were studied. BMI, waist cm and hypertension were compared between those on drugs prescribed for chronic pain and CM drugs to those on CM drugs only. Multiple confounders were controlled for.

The impact of medications for chronic pain and sleep upon CM health and obesity is of concern for these classes of drugs which have been recently labelled as dependency forming medications. The results from this cross sectional study warrants further investigation and adds further support to calls for these medications to be prescribed for shorter periods.

@article{Bradbury2017b,
title = {Dietary Intake of High-Protein Foods and Other Major Foods in Meat-Eaters, Poultry-Eaters, Fish-Eaters, Vegetarians, and Vegans in UK Biobank.},
author = {KE Bradbury and TYN Tong and TJ Key},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29207491},
year = {2017},
date = {2017-12-02},
journal = {Nutrients },
abstract = {Vegetarian diets are defined by the absence of meat and fish, but differences in the intake of other foods between meat-eaters and low or non-meat eaters are also important to document. We examined intakes of high-protein foods (meat, poultry, fish, legumes, nuts, vegetarian protein alternatives, dairy products, and eggs) and other major food groups (fruit, vegetables, bread, pasta, rice, snack foods, and beverages) in regular meat-eaters, low meat-eaters, poultry-eaters, fish-eaters, vegetarians, and vegans of white ethnicity participating in UK Biobank who had completed at least one web-based 24-h dietary assessment (n = 199,944). In regular meat-eaters, around 25% of total energy came from meat, fish, dairy and plant milk, cheese, yogurt, and eggs. In vegetarians, around 20% of energy came from dairy and plant milk, cheese, yoghurt, eggs, legumes, nuts, and vegetarian protein alternatives, and in vegans around 15% came from plant milk, legumes, vegetarian alternatives, and nuts. Low and non-meat eaters had higher intakes of fruit and vegetables and lower intakes of roast or fried potatoes compared to regular meat-eaters. The differences in the intakes of meat, plant-based high-protein foods, and other foods between meat-eaters and low and non-meat eaters in UK Biobank may contribute to differences in health outcomes.},
keywords = {3037, diet},
pubstate = {published},
tppubtype = {article}
}

Vegetarian diets are defined by the absence of meat and fish, but differences in the intake of other foods between meat-eaters and low or non-meat eaters are also important to document. We examined intakes of high-protein foods (meat, poultry, fish, legumes, nuts, vegetarian protein alternatives, dairy products, and eggs) and other major food groups (fruit, vegetables, bread, pasta, rice, snack foods, and beverages) in regular meat-eaters, low meat-eaters, poultry-eaters, fish-eaters, vegetarians, and vegans of white ethnicity participating in UK Biobank who had completed at least one web-based 24-h dietary assessment (n = 199,944). In regular meat-eaters, around 25% of total energy came from meat, fish, dairy and plant milk, cheese, yogurt, and eggs. In vegetarians, around 20% of energy came from dairy and plant milk, cheese, yoghurt, eggs, legumes, nuts, and vegetarian protein alternatives, and in vegans around 15% came from plant milk, legumes, vegetarian alternatives, and nuts. Low and non-meat eaters had higher intakes of fruit and vegetables and lower intakes of roast or fried potatoes compared to regular meat-eaters. The differences in the intakes of meat, plant-based high-protein foods, and other foods between meat-eaters and low and non-meat eaters in UK Biobank may contribute to differences in health outcomes.

We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies.
Results:

Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption.
Conclusions:

There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake.
Methods:

We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies.
Results:

Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption.
Conclusions:

Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking.

@article{Thomas2017,
title = {Frequency and phenotype of type 1 diabetes in the first six decades of life: a cross-sectional, genetically stratified survival analysis from UK Biobank},
author = { Nicholas J Thomas and Samuel E Jones PhD and Michael N Weedon PhD and Beverley M Shields PhD and Richard A Oram PhD and Prof Andrew T Hattersley},
url = {http://www.thelancet.com/journals/landia/article/PIIS2213-8587(17)30362-5/fulltext},
year = {2017},
date = {2017-11-30},
journal = {The Lancet Diabetes and Endocrinology},
abstract = {Type 1 diabetes is typically considered a disease of children and young adults. Genetic susceptibility to young-onset type 1 diabetes is well defined and does not predispose to type 2 diabetes. It is not known how frequently genetic susceptibility to type 1 diabetes leads to a diagnosis of diabetes after age 30 years. We aimed to investigate the frequency and phenotype of type 1 diabetes resulting from high genetic susceptibility in the first six decades of life.

Methods

In this cross-sectional analysis, we used a type 1 diabetes genetic risk score based on 29 common variants to identify individuals of white European descent in UK Biobank in the half of the population with high or low genetic susceptibility to type 1 diabetes. We used Kaplan-Meier analysis to evaluate the number of cases of diabetes in both groups in the first six decades of life. We genetically defined type 1 diabetes as the additional cases of diabetes that occurred in the high genetic susceptibility group compared with the low genetic susceptibility group. All remaining cases were defined as type 2 diabetes. We assessed the clinical characteristics of the groups with genetically defined type 1 or type 2 diabetes.

Findings

13 250 (3·5%) of 379 511 white European individuals in UK Biobank had developed diabetes in the first six decades of life. 1286 more cases of diabetes were in the half of the population with high genetic susceptibility to type 1 diabetes than in the half of the population with low genetic susceptibility. These genetically defined cases of type 1 diabetes were distributed across all ages of diagnosis; 537 (42%) were in individuals diagnosed when aged 31–60 years, representing 4% (537/12 233) of all diabetes cases diagnosed after age 30 years. The clinical characteristics of the group diagnosed with type 1 diabetes when aged 31–60 years were similar to the clinical characteristics of the group diagnosed with type 1 diabetes when aged 30 years or younger. For individuals diagnosed with diabetes when aged 31–60 years, the clinical characteristics of type 1 diabetes differed from those of type 2 diabetes: they had a lower BMI (27·4 kg/m2 [95% CI 26·7–28·0] vs 32·4 kg/m2 [32·2–32·5]; p<0·0001), were more likely to use insulin in the first year after diagnosis (89% [476/537] vs 6% [648/11 696]; p<0·0001), and were more likely to have diabetic ketoacidosis (11% [61/537] vs 0·3% [30/11 696]; p<0·0001).

Interpretation

Genetic susceptibility to type 1 diabetes results in non-obesity-related, insulin-dependent diabetes, which presents throughout the first six decades of life. Our results highlight the difficulty of identifying type 1 diabetes after age 30 years because of the increasing background prevalence of type 2 diabetes. Failure to diagnose late-onset type 1 diabetes can have serious consequences because these patients rapidly develop insulin dependency.
Funding

Type 1 diabetes is typically considered a disease of children and young adults. Genetic susceptibility to young-onset type 1 diabetes is well defined and does not predispose to type 2 diabetes. It is not known how frequently genetic susceptibility to type 1 diabetes leads to a diagnosis of diabetes after age 30 years. We aimed to investigate the frequency and phenotype of type 1 diabetes resulting from high genetic susceptibility in the first six decades of life.

Methods

In this cross-sectional analysis, we used a type 1 diabetes genetic risk score based on 29 common variants to identify individuals of white European descent in UK Biobank in the half of the population with high or low genetic susceptibility to type 1 diabetes. We used Kaplan-Meier analysis to evaluate the number of cases of diabetes in both groups in the first six decades of life. We genetically defined type 1 diabetes as the additional cases of diabetes that occurred in the high genetic susceptibility group compared with the low genetic susceptibility group. All remaining cases were defined as type 2 diabetes. We assessed the clinical characteristics of the groups with genetically defined type 1 or type 2 diabetes.

Findings

13 250 (3·5%) of 379 511 white European individuals in UK Biobank had developed diabetes in the first six decades of life. 1286 more cases of diabetes were in the half of the population with high genetic susceptibility to type 1 diabetes than in the half of the population with low genetic susceptibility. These genetically defined cases of type 1 diabetes were distributed across all ages of diagnosis; 537 (42%) were in individuals diagnosed when aged 31–60 years, representing 4% (537/12 233) of all diabetes cases diagnosed after age 30 years. The clinical characteristics of the group diagnosed with type 1 diabetes when aged 31–60 years were similar to the clinical characteristics of the group diagnosed with type 1 diabetes when aged 30 years or younger. For individuals diagnosed with diabetes when aged 31–60 years, the clinical characteristics of type 1 diabetes differed from those of type 2 diabetes: they had a lower BMI (27·4 kg/m2 [95% CI 26·7–28·0] vs 32·4 kg/m2 [32·2–32·5]; p<0·0001), were more likely to use insulin in the first year after diagnosis (89% [476/537] vs 6% [648/11 696]; p<0·0001), and were more likely to have diabetic ketoacidosis (11% [61/537] vs 0·3% [30/11 696]; p<0·0001).

Interpretation

Genetic susceptibility to type 1 diabetes results in non-obesity-related, insulin-dependent diabetes, which presents throughout the first six decades of life. Our results highlight the difficulty of identifying type 1 diabetes after age 30 years because of the increasing background prevalence of type 2 diabetes. Failure to diagnose late-onset type 1 diabetes can have serious consequences because these patients rapidly develop insulin dependency.
Funding

Mood instability is a core clinical feature of affective and psychotic disorders. In keeping with the Research Domain Criteria approach, it may be a useful construct for identifying biology that cuts across psychiatric categories. We aimed to investigate the biological validity of a simple measure of mood instability and evaluate its genetic relationship with several psychiatric disorders, including major depressive disorder (MDD), bipolar disorder (BD), schizophrenia, attention deficit hyperactivity disorder (ADHD), anxiety disorder and post-traumatic stress disorder (PTSD). We conducted a genome-wide association study (GWAS) of mood instability in 53,525 cases and 60,443 controls from UK Biobank, identifying four independently associated loci (on chromosomes 8, 9, 14 and 18), and a common single-nucleotide polymorphism (SNP)-based heritability estimate of ~8%. We found a strong genetic correlation between mood instability and MDD (rg = 0.60, SE = 0.07, p = 8.95 × 10−17) and a small but significant genetic correlation with both schizophrenia (rg = 0.11, SE = 0.04, p = 0.01) and anxiety disorders (rg = 0.28, SE = 0.14, p = 0.04), although no genetic correlation with BD, ADHD or PTSD was observed. Several genes at the associated loci may have a role in mood instability, including the DCC netrin 1 receptor (DCC) gene, eukaryotic translation initiation factor 2B subunit beta (eIF2B2), placental growth factor (PGF) and protein tyrosine phosphatase, receptor type D (PTPRD). Strengths of this study include the very large sample size, but our measure of mood instability may be limited by the use of a single question. Overall, this work suggests a polygenic basis for mood instability. This simple measure can be obtained in very large samples; our findings suggest that doing so may offer the opportunity to illuminate the fundamental biology of mood regulation.

Genome-wide association studies using genotype data have had limited success in the identification of variants associated with major depressive disorder (MDD). Haplotype data provide an alternative method for detecting associations between variants in weak linkage disequilibrium with genotyped variants and a given trait of interest. A genome-wide haplotype association study for MDD was undertaken utilising a family-based population cohort, Generation Scotland: Scottish Family Health Study (n = 18,773), as a discovery cohort with UK Biobank used as a population-based replication cohort (n = 25,035). Fine mapping of haplotype boundaries was used to account for overlapping haplotypes potentially tagging the same causal variant. Within the discovery cohort, two haplotypes exceeded genome-wide significance (P < 5 × 10−8) for an association with MDD. One of these haplotypes was nominally significant in the replication cohort (P < 0.05) and was located in 6q21, a region which has been previously associated with bipolar disorder, a psychiatric disorder that is phenotypically and genetically correlated with MDD. Several haplotypes with P < 10−7 in the discovery cohort were located within gene coding regions associated with diseases that are comorbid with MDD. Using such haplotypes to highlight regions for sequencing may lead to the identification of the underlying causal variants.

Background: There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images.
Methods: Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts.
Results: Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%).
Conclusions: Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of participants and burdening of publicly-funded health services suggests that radiographer flagging is a justifiable approach in the UK Biobank imaging study. The potential scale of non-serious final diagnoses raises questions relating to handling IFs in other settings, such as commercial and public health screening.

@article{Pirastu2017,
title = {GWAS for male-pattern baldness identifies 71 susceptibility loci explaining 38% of the risk},
author = {Nicola Pirastu and Peter K. Joshi and Paul S. de Vries and Marilyn C. Cornelis and Paul M. McKeigue and NaNa Keum and Nora Franceschini and Marco Colombo and Edward L. Giovannucci and Athina Spiliopoulou and Lude Franke and Kari E. North and Peter Kraft and Alanna C. Morrison and Tõnu Esko and James F. Wilson},
url = {https://www.nature.com/articles/s41467-017-01490-8},
year = {2017},
date = {2017-11-17},
journal = {Nature Communications},
abstract = {Male pattern baldness (MPB) or androgenetic alopecia is one of the most common conditions affecting men, reaching a prevalence of ~50% by the age of 50; however, the known genes explain little of the heritability. Here, we present the results of a genome-wide association study including more than 70,000 men, identifying 71 independently replicated loci, of which 30 are novel. These loci explain 38% of the risk, suggesting that MPB is less genetically complex than other complex traits. We show that many of these loci contain genes that are relevant to the pathology and highlight pathways and functions underlying baldness. Finally, despite only showing genome-wide genetic correlation with height, pathway-specific genetic correlations are significant for traits including lifespan and cancer. Our study not only greatly increases the number of MPB loci, illuminating the genetic architecture, but also provides a new approach to disentangling the shared biological pathways underlying complex diseases.},
keywords = {24661, baldness, featured, genetics},
pubstate = {published},
tppubtype = {article}
}

Male pattern baldness (MPB) or androgenetic alopecia is one of the most common conditions affecting men, reaching a prevalence of ~50% by the age of 50; however, the known genes explain little of the heritability. Here, we present the results of a genome-wide association study including more than 70,000 men, identifying 71 independently replicated loci, of which 30 are novel. These loci explain 38% of the risk, suggesting that MPB is less genetically complex than other complex traits. We show that many of these loci contain genes that are relevant to the pathology and highlight pathways and functions underlying baldness. Finally, despite only showing genome-wide genetic correlation with height, pathway-specific genetic correlations are significant for traits including lifespan and cancer. Our study not only greatly increases the number of MPB loci, illuminating the genetic architecture, but also provides a new approach to disentangling the shared biological pathways underlying complex diseases.

The brain white matter intracellular volume fraction was significantly lower, and isotropic volume fraction was higher in hypertensive relative to non-hypertensive individuals (N = 1559, each). The white matter isotropic volume fraction also was higher in pre-hypertensive than in normotensive individuals (N = 694, each) in the right superior longitudinal fasciculus and the right superior thalamic radiation, where the lower intracellular volume fraction was observed in the hypertensives relative to the non-hypertensive group.

The brain white matter intracellular volume fraction was significantly lower, and isotropic volume fraction was higher in hypertensive relative to non-hypertensive individuals (N = 1559, each). The white matter isotropic volume fraction also was higher in pre-hypertensive than in normotensive individuals (N = 694, each) in the right superior longitudinal fasciculus and the right superior thalamic radiation, where the lower intracellular volume fraction was observed in the hypertensives relative to the non-hypertensive group.

Background -The long-term probability of developing atrial fibrillation (AF) considering genetic predisposition and clinical risk factor burden is unknown. Methods -We estimated lifetime risk of AF in individuals from the community-based Framingham Heart Study. Polygenic risk for AF was derived using a score of approximately 1,000 AF-associated single nucleotide polymorphisms. Clinical risk factor burden was calculated for each individual using a validated risk score for incident AF comprised of height, weight, systolic and diastolic blood pressure, current smoking status, antihypertensive medication use, diabetes, history of myocardial infarction, and history of heart failure. We estimated the lifetime risk of AF within tertiles of polygenic and clinical risk. Results -Among 4,606 participants without AF at age 55 years, 580 developed incident AF (median follow-up, 9.4 years; 25th-75th percentile, 4.4-14.3 years). The lifetime risk of AF after age 55 years was 37.1%, and was substantially influenced by both polygenic and clinical risk factor burden. Among individuals free of AF at age 55 years, those in low polygenic and clinical risk tertiles had a lifetime risk of AF of 22.3% (95% confidence interval [CI], 15.4%-29.1%), whereas those in high risk tertiles had a risk of 48.2% (95% CI, 41.3%-55.1%). A lower clinical risk factor burden was associated with later AF onset after adjusting for genetic predisposition (P value <0.001). Conclusions -In our community-based cohort, the lifetime risk of AF was 37%. Estimation of polygenic AF risk is feasible, and together with clinical risk factor burden explains a substantial gradient in long-term AF risk.

@article{Marquez-Luna2017,
title = {Multiethnic polygenic risk scores improve risk prediction in diverse populations},
author = {C Marquez-Luna and P Loh and A L Price},
url = {http://onlinelibrary.wiley.com/doi/10.1002/gepi.22083/abstract},
year = {2017},
date = {2017-11-07},
journal = {Genetic Epidemiology},
abstract = {Methods for genetic risk prediction have been widely investigated in recent years. However, most available training data involves European samples, and it is currently unclear how to accurately predict disease risk in other populations. Previous studies have used either training data from European samples in large sample size or training data from the target population in small sample size, but not both. Here, we introduce a multiethnic polygenic risk score that combines training data from European samples and training data from the target population. We applied this approach to predict type 2 diabetes (T2D) in a Latino cohort using both publicly available European summary statistics in large sample size (Neff = 40k) and Latino training data in small sample size (Neff = 8k). Here, we attained a >70% relative improvement in prediction accuracy (from R2 = 0.027 to 0.047) compared to methods that use only one source of training data, consistent with large relative improvements in simulations. We observed a systematically lower load of T2D risk alleles in Latino individuals with more European ancestry, which could be explained by polygenic selection in ancestral European and/or Native American populations. We predict T2D in a South Asian UK Biobank cohort using European (Neff = 40k) and South Asian (Neff = 16k) training data and attained a >70% relative improvement in prediction accuracy, and application to predict height in an African UK Biobank cohort using European (N = 113k) and African (N = 2k) training data attained a 30% relative improvement. Our work reduces the gap in polygenic risk prediction accuracy between European and non-European target populations.},
keywords = {16549, genetics},
pubstate = {published},
tppubtype = {article}
}

Methods for genetic risk prediction have been widely investigated in recent years. However, most available training data involves European samples, and it is currently unclear how to accurately predict disease risk in other populations. Previous studies have used either training data from European samples in large sample size or training data from the target population in small sample size, but not both. Here, we introduce a multiethnic polygenic risk score that combines training data from European samples and training data from the target population. We applied this approach to predict type 2 diabetes (T2D) in a Latino cohort using both publicly available European summary statistics in large sample size (Neff = 40k) and Latino training data in small sample size (Neff = 8k). Here, we attained a >70% relative improvement in prediction accuracy (from R2 = 0.027 to 0.047) compared to methods that use only one source of training data, consistent with large relative improvements in simulations. We observed a systematically lower load of T2D risk alleles in Latino individuals with more European ancestry, which could be explained by polygenic selection in ancestral European and/or Native American populations. We predict T2D in a South Asian UK Biobank cohort using European (Neff = 40k) and South Asian (Neff = 16k) training data and attained a >70% relative improvement in prediction accuracy, and application to predict height in an African UK Biobank cohort using European (N = 113k) and African (N = 2k) training data attained a 30% relative improvement. Our work reduces the gap in polygenic risk prediction accuracy between European and non-European target populations.

Community cohort participants (UK Biobank n = 502 637) aged 37–73 years were recruited between 2006 and 2010. Self-reported LTCs (n = 42) identified in people with AF at baseline. All-cause mortality was available for a median follow-up of 7 years (interquartile range 76–93 months). Hazard ratios (HRs) examined associations between number and type of co-morbid LTC and all-cause mortality, adjusting for age, sex, socio-economic status, smoking, and anticoagulation status. Three thousand six hundred fifty-one participants (0.7% of the study population) reported AF; mean age was 61.9 years. The all-cause mortality rate was 6.7% (248 participants) at 7 years. Atrial fibrillation participants with ≥4 co-morbidities had a six-fold higher risk of mortality compared to participants without any LTC. Co-morbid heart failure was associated with higher risk of mortality [HR 2.96, 95% confidence interval (CI) 1.83–4.80], whereas the presence of co-morbid stroke did not have a significant association. Among non-cardiometabolic conditions, presence of chronic obstructive pulmonary disease (HR 3.31, 95% CI 2.14–5.11) and osteoporosis (HR 3.13, 95% CI 1.63–6.01) was associated with a higher risk of mortality.

Conclusion

Survival in middle-aged to older individuals with self-reported AF is strongly correlated with level of multimorbidity. This group should be targeted for interventions to optimize their management, which in turn may potentially reduce the impact of their co-morbidities on survival. Future AF clinical guidelines need to place greater emphasis on the issue of co-morbidity.},
keywords = {14151, atrial fibrillation, featured, morbidity},
pubstate = {published},
tppubtype = {article}
}

To examine the number and type of co-morbid long-term health conditions (LTCs) and their associations with all-cause mortality in an atrial fibrillation (AF) population.

Methods and results

Community cohort participants (UK Biobank n = 502 637) aged 37–73 years were recruited between 2006 and 2010. Self-reported LTCs (n = 42) identified in people with AF at baseline. All-cause mortality was available for a median follow-up of 7 years (interquartile range 76–93 months). Hazard ratios (HRs) examined associations between number and type of co-morbid LTC and all-cause mortality, adjusting for age, sex, socio-economic status, smoking, and anticoagulation status. Three thousand six hundred fifty-one participants (0.7% of the study population) reported AF; mean age was 61.9 years. The all-cause mortality rate was 6.7% (248 participants) at 7 years. Atrial fibrillation participants with ≥4 co-morbidities had a six-fold higher risk of mortality compared to participants without any LTC. Co-morbid heart failure was associated with higher risk of mortality [HR 2.96, 95% confidence interval (CI) 1.83–4.80], whereas the presence of co-morbid stroke did not have a significant association. Among non-cardiometabolic conditions, presence of chronic obstructive pulmonary disease (HR 3.31, 95% CI 2.14–5.11) and osteoporosis (HR 3.13, 95% CI 1.63–6.01) was associated with a higher risk of mortality.

Conclusion

Survival in middle-aged to older individuals with self-reported AF is strongly correlated with level of multimorbidity. This group should be targeted for interventions to optimize their management, which in turn may potentially reduce the impact of their co-morbidities on survival. Future AF clinical guidelines need to place greater emphasis on the issue of co-morbidity.

@article{Cai2017,
title = {Ambient air pollution, traffic noise and adult asthma prevalence: a BioSHaRE approach},
author = {Yutong Cai and Wilma L. Zijlema and Dany Doiron and Marta Blangiardo and Paul R. Burton and Isabel Fortier and Amadou Gaye and John Gulliver and Kees de Hoogh and Kristian Hveem and Stéphane Mbatchou and David W. Morley and Ronald P. Stolk and Paul Elliott and Anna L. Hansell and Susan Hodgson},
url = {http://erj.ersjournals.com/content/early/2016/10/20/13993003.02127-2015},
year = {2017},
date = {2017-11-01},
journal = {European Respiratory Journal 2016},
abstract = {We investigated the effects of both ambient air pollution and traffic noise on adult asthma prevalence, using harmonised data from three European cohort studies established in 2006–2013 (HUNT3, Lifelines and UK Biobank).

Residential exposures to ambient air pollution (particulate matter with aerodynamic diameter ≤10 µm (PM10) and nitrogen dioxide (NO2)) were estimated by a pan-European Land Use Regression model for 2007. Traffic noise for 2009 was modelled at home addresses by adapting a standardised noise assessment framework (CNOSSOS-EU). A cross-sectional analysis of 646 731 participants aged ≥20 years was undertaken using DataSHIELD to pool data for individual-level analysis via a “compute to the data” approach. Multivariate logistic regression models were fitted to assess the effects of each exposure on lifetime and current asthma prevalence.

PM10 or NO2 higher by 10 µg·m−3 was associated with 12.8% (95% CI 9.5–16.3%) and 1.9% (95% CI 1.1–2.8%) higher lifetime asthma prevalence, respectively, independent of confounders. Effects were larger in those aged ≥50 years, ever-smokers and less educated. Noise exposure was not significantly associated with asthma prevalence.

This study suggests that long-term ambient PM10 exposure is associated with asthma prevalence in western European adults. Traffic noise is not associated with asthma prevalence, but its potential to impact on asthma exacerbations needs further investigation.},
keywords = {5179, air pollution, asthma, featured},
pubstate = {published},
tppubtype = {article}
}

We investigated the effects of both ambient air pollution and traffic noise on adult asthma prevalence, using harmonised data from three European cohort studies established in 2006–2013 (HUNT3, Lifelines and UK Biobank).

Residential exposures to ambient air pollution (particulate matter with aerodynamic diameter ≤10 µm (PM10) and nitrogen dioxide (NO2)) were estimated by a pan-European Land Use Regression model for 2007. Traffic noise for 2009 was modelled at home addresses by adapting a standardised noise assessment framework (CNOSSOS-EU). A cross-sectional analysis of 646 731 participants aged ≥20 years was undertaken using DataSHIELD to pool data for individual-level analysis via a “compute to the data” approach. Multivariate logistic regression models were fitted to assess the effects of each exposure on lifetime and current asthma prevalence.

PM10 or NO2 higher by 10 µg·m−3 was associated with 12.8% (95% CI 9.5–16.3%) and 1.9% (95% CI 1.1–2.8%) higher lifetime asthma prevalence, respectively, independent of confounders. Effects were larger in those aged ≥50 years, ever-smokers and less educated. Noise exposure was not significantly associated with asthma prevalence.

This study suggests that long-term ambient PM10 exposure is associated with asthma prevalence in western European adults. Traffic noise is not associated with asthma prevalence, but its potential to impact on asthma exacerbations needs further investigation.

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

@article{Welch2017,
title = {Dietary Magnesium May Be Protective for Aging of Bone and Skeletal Muscle in Middle and Younger Older Age Men and Women: Cross-Sectional Findings from the UK Biobank Cohort.},
author = {AA Welch and J Skinner and M Hickson},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29084183},
year = {2017},
date = {2017-10-30},
journal = {Nutrients},
abstract = {Although fragility fractures, osteoporosis, sarcopenia, and frailty are becoming more prevalent in our aging society the treatment options are limited and preventative strategies are needed. Despite magnesium being integral to bone and muscle physiology, the relationship between dietary magnesium and skeletal muscle and bone health has not been investigated concurrently to date. We analysed cross-sectional associations between dietary magnesium and skeletal muscle mass (as fat free mass-FFM), grip strength, and bone density (BMD) in 156,575 men and women aged 39-72 years from the UK Biobank cohort. FFM was measured with bioelectrical impedance and was expressed as the percentage of body weight (FFM%) or as divided by body mass index (FFMBMI). Adjusted mean grip strength, FFM%, FFMBMI, and BMD were calculated according to quintiles of dietary magnesium, while correcting for covariates. Significant inter-quintile differences across intakes of magnesium existed in men and women, respectively, of 1.1% and 2.4% for grip strength, 3.0% and 3.6% for FFM%, 5.1% and 5.5% for FFMBMI, and 2.9% and 0.9% for BMD. These associations are as great or greater than annual measured losses of these musculoskeletal outcomes, indicating potential clinical significance. Our study suggests that dietary magnesium may play a role in musculoskeletal health and has relevance for population prevention strategies for sarcopenia, osteoporosis, and fractures.},
keywords = {11058, diet, osteoporosis},
pubstate = {published},
tppubtype = {article}
}

Although fragility fractures, osteoporosis, sarcopenia, and frailty are becoming more prevalent in our aging society the treatment options are limited and preventative strategies are needed. Despite magnesium being integral to bone and muscle physiology, the relationship between dietary magnesium and skeletal muscle and bone health has not been investigated concurrently to date. We analysed cross-sectional associations between dietary magnesium and skeletal muscle mass (as fat free mass-FFM), grip strength, and bone density (BMD) in 156,575 men and women aged 39-72 years from the UK Biobank cohort. FFM was measured with bioelectrical impedance and was expressed as the percentage of body weight (FFM%) or as divided by body mass index (FFMBMI). Adjusted mean grip strength, FFM%, FFMBMI, and BMD were calculated according to quintiles of dietary magnesium, while correcting for covariates. Significant inter-quintile differences across intakes of magnesium existed in men and women, respectively, of 1.1% and 2.4% for grip strength, 3.0% and 3.6% for FFM%, 5.1% and 5.5% for FFMBMI, and 2.9% and 0.9% for BMD. These associations are as great or greater than annual measured losses of these musculoskeletal outcomes, indicating potential clinical significance. Our study suggests that dietary magnesium may play a role in musculoskeletal health and has relevance for population prevention strategies for sarcopenia, osteoporosis, and fractures.

In: Nature Genetics, 2017, (MA Ferreira and JM Vonk and H Baurecht and I Marenholz and C Tian and JD Hoffman and Q Helmer and A Tillander and V Ullemar and J van Dongen and Y Lu and F Rüschendorf and J Esparza-Gordillo and CW Medway and E Mountjoy and K Burrows and O Hummel and S Grosche and BM Brumpton and JS Witte and JJ Hottenga and G Willemsen and J Zheng and E Rodríguez and M Hotze and A Franke and JA Revez and J Beesley and MC Matheson and SC Dharmage and LM Bain and LG Fritsche and ME Gabrielsen and B Balliu and 23andMe Research Team and AAGC collaborators and BIOS consortium and LifeLines Cohort Study and JB Nielsen and W Zhou and K Hveem and A Langhammer and OL Holmen and M Løset and GR Abecasis and CJ Willer and A Arnold and G Homuth and CO Schmidt and PJ Thompson and NG Martin and DL Duffy and N Novak and H Schulz and S Karrasch and C Gieger and and K Strauch and RB Melles DA Hinds and N Hübner and S Weidinger and PKE Magnusson and R Jansen and E Jorgenson and YA Lee and D Boomsma and C Almqvist and R Karlsson and GH Koppelman and L Paternoster.).

Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals, partly because of a shared genetic origin. To identify shared risk variants, we performed a genome-wide association study (GWAS; n = 360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P < 3 × 10-8), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes.

@article{Firth2017,
title = {The Validity and Value of Self-reported Physical Activity and Accelerometry in People With Schizophrenia: A Population-Scale Study of the UK Biobank},
author = { Joseph Firth and Brendon Stubbs and Davy Vancampfort and Felipe B Schuch and Simon Rosenbaum and Philip B Ward and Josh A Firth and Jerome Sarris and Alison R Yung},
url = {https://academic.oup.com/schizophreniabulletin/article/4563831/The-Validity-and-Value-of-Self-reported-Physical},
year = {2017},
date = {2017-10-24},
journal = {Schizophrenia Bulletin},
abstract = {Previous physical activity (PA) research in schizophrenia has relied largely upon self-report measures. However, the accuracy of this method is questionable. Obtaining accurate measurements, and determining what may influence PA levels in schizophrenia, is essential to understand physical inactivity in this population. This study examined differences in self-reported and objectively measured PA in people with schizophrenia and the general population using a large, population-based dataset from the UK Biobank.
Methods

Baseline data from the UK Biobank (2007–2010) were analyzed; including 1078 people with schizophrenia (54.19 ± 8.39 years; 55% male) and 450549 without (56.44 ± 8.11; 46% male). We compared self-reported PA with objectively measured accelerometry data in schizophrenia and comparison samples. We also examined correlations between self-report and objective measures.
Results

People with schizophrenia reported the same PA levels as those without, with no differences in low, moderate, or vigorous intensity activity. However, accelerometry data showed a large and statistically significant reduction of PA in schizophrenia; as people with schizophrenia, on average, engaged in less PA than 80% of the general population. Nonetheless, within the schizophrenia sample, total self-reported PA still held significant correlations with objective measures.
Conclusions

People with schizophrenia are significantly less active than the general population. However, self-report measures in epidemiological studies fail to capture the reduced activity levels in schizophrenia. This also has implications for self-report measures of other lifestyle factors which may contribute toward the poor health outcomes observed in schizophrenia. Nonetheless, self-report measures may still be useful for identifying how active individuals with schizophrenia relative to other patients.},
keywords = {22125, exercise, featured, schizophrenia},
pubstate = {published},
tppubtype = {article}
}

Previous physical activity (PA) research in schizophrenia has relied largely upon self-report measures. However, the accuracy of this method is questionable. Obtaining accurate measurements, and determining what may influence PA levels in schizophrenia, is essential to understand physical inactivity in this population. This study examined differences in self-reported and objectively measured PA in people with schizophrenia and the general population using a large, population-based dataset from the UK Biobank.
Methods

Baseline data from the UK Biobank (2007–2010) were analyzed; including 1078 people with schizophrenia (54.19 ± 8.39 years; 55% male) and 450549 without (56.44 ± 8.11; 46% male). We compared self-reported PA with objectively measured accelerometry data in schizophrenia and comparison samples. We also examined correlations between self-report and objective measures.
Results

People with schizophrenia reported the same PA levels as those without, with no differences in low, moderate, or vigorous intensity activity. However, accelerometry data showed a large and statistically significant reduction of PA in schizophrenia; as people with schizophrenia, on average, engaged in less PA than 80% of the general population. Nonetheless, within the schizophrenia sample, total self-reported PA still held significant correlations with objective measures.
Conclusions

People with schizophrenia are significantly less active than the general population. However, self-report measures in epidemiological studies fail to capture the reduced activity levels in schizophrenia. This also has implications for self-report measures of other lifestyle factors which may contribute toward the poor health outcomes observed in schizophrenia. Nonetheless, self-report measures may still be useful for identifying how active individuals with schizophrenia relative to other patients.

@article{Alfaro-Almagro2017,
title = {Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank.},
author = {F Alfaro-Almagro and M Jenkinson and NK Bangerter and JLR Andersson and L Griffanti and G Douaud SN Sotiropoulos and S Jbabdi and M Hernandez-Fernandez and E Vallee and D Vidaurre and M Webster and P McCarthy and C Rorden and A Daducci and DC Alexander and H Zhang and I Dragonu and PM Matthews and KL Miller and SM Smith },
url = {https://www.ncbi.nlm.nih.gov/pubmed/29079522},
year = {2017},
date = {2017-10-24},
journal = {NeuroImage},
abstract = {UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.},
keywords = {8107, brain imaging, featured, methodology},
pubstate = {published},
tppubtype = {article}
}

UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with high mortality, uncertain cause, and few treatment options. Studies have identified a significant genetic risk associated with the development of IPF; however, mechanisms by which genetic risk factors promote IPF remain unclear. We aimed to identify genetic variants associated with IPF susceptibility and provide mechanistic insight using gene and protein expression analyses.

Methods

We used a two-stage approach: a genome-wide association study in patients with IPF of European ancestry recruited from nine different centres in the UK and controls selected from UK Biobank (stage 1) matched for age, sex, and smoking status; and a follow-up of associated genetic variants in independent datasets of patients with IPF and controls from two independent US samples from the Chicago consortium and the Colorado consortium (stage 2). We investigated the effect of novel signals on gene expression in large transcriptomic and genomic data resources, and examined expression using lung tissue samples from patients with IPF and controls.

Findings

602 patients with IPF and 3366 controls were selected for stage 1. For stage 2, 2158 patients with IPF and 5195 controls were selected. We identified a novel genome-wide significant signal of association with IPF susceptibility near A-kinase anchoring protein 13 (AKAP13; rs62025270, odds ratio [OR] 1·27 [95% CI 1·18–1·37], p=1·32 × 10−9) and confirmed previously reported signals, including in mucin 5B (MUC5B; rs35705950, OR 2·89 [2·56–3·26], p=1·12 × 10−66) and desmoplakin (DSP; rs2076295, OR 1·44 [1·35–1·54], p=7·81 × 10−28). For rs62025270, the allele A associated with increased susceptibility to IPF was also associated with increased expression of AKAP13 mRNA in lung tissue from patients who had lung resection procedures (n=1111). We showed that AKAP13 is expressed in the alveolar epithelium and lymphoid follicles from patients with IPF, and AKAP13 mRNA expression was 1·42-times higher in lung tissue from patients with IPF (n=46) than that in lung tissue from controls (n=51).

Interpretation

AKAP13 is a Rho guanine nucleotide exchange factor regulating activation of RhoA, which is known to be involved in profibrotic signalling pathways. The identification of AKAP13 as a susceptibility gene for IPF increases the prospect of successfully targeting RhoA pathway inhibitors in patients with IPF.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with high mortality, uncertain cause, and few treatment options. Studies have identified a significant genetic risk associated with the development of IPF; however, mechanisms by which genetic risk factors promote IPF remain unclear. We aimed to identify genetic variants associated with IPF susceptibility and provide mechanistic insight using gene and protein expression analyses.

Methods

We used a two-stage approach: a genome-wide association study in patients with IPF of European ancestry recruited from nine different centres in the UK and controls selected from UK Biobank (stage 1) matched for age, sex, and smoking status; and a follow-up of associated genetic variants in independent datasets of patients with IPF and controls from two independent US samples from the Chicago consortium and the Colorado consortium (stage 2). We investigated the effect of novel signals on gene expression in large transcriptomic and genomic data resources, and examined expression using lung tissue samples from patients with IPF and controls.

Findings

602 patients with IPF and 3366 controls were selected for stage 1. For stage 2, 2158 patients with IPF and 5195 controls were selected. We identified a novel genome-wide significant signal of association with IPF susceptibility near A-kinase anchoring protein 13 (AKAP13; rs62025270, odds ratio [OR] 1·27 [95% CI 1·18–1·37], p=1·32 × 10−9) and confirmed previously reported signals, including in mucin 5B (MUC5B; rs35705950, OR 2·89 [2·56–3·26], p=1·12 × 10−66) and desmoplakin (DSP; rs2076295, OR 1·44 [1·35–1·54], p=7·81 × 10−28). For rs62025270, the allele A associated with increased susceptibility to IPF was also associated with increased expression of AKAP13 mRNA in lung tissue from patients who had lung resection procedures (n=1111). We showed that AKAP13 is expressed in the alveolar epithelium and lymphoid follicles from patients with IPF, and AKAP13 mRNA expression was 1·42-times higher in lung tissue from patients with IPF (n=46) than that in lung tissue from controls (n=51).

Interpretation

AKAP13 is a Rho guanine nucleotide exchange factor regulating activation of RhoA, which is known to be involved in profibrotic signalling pathways. The identification of AKAP13 as a susceptibility gene for IPF increases the prospect of successfully targeting RhoA pathway inhibitors in patients with IPF.

Funding

UK Medical Research Council, National Heart, Lung, and Blood Institute of the US National Institutes of Health, Agencia Canaria de Investigación, Innovación y Sociedad de la Información, Spain, UK National Institute for Health Research, and the British Lung Foundation

@article{Maddock2017,
title = {Vitamin D and cognitive function: A Mendelian randomisation study},
author = {Jane Maddock and Ang Zhou and Alana Cavadino and Elżbieta Kuźma and Yanchun Bao and Melissa C. Smart and Kai-Uwe Saum and Ben Schöttker and Jorgen Engmann and Marie Kjærgaard and Ville Karhunen and Yiqiang Zhan and Terho Lehtimäki and Suvi P. Rovio and Liisa Byberg and Jari Lahti and Pedro Marques-Vidal and Abhijit Sen and Laura Perna and Henrik Schirmer and Archana Singh-Manoux and Juha Auvinen and Nina Hutri-Kähönen and Mika Kähönen and Lena Kilander and Katri Räikkönen and Håkan Melhus and Erik Ingelsson and Idris Guessous and Katja E Petrovic and Helena Schmidt and Reinhold Schmidt and Peter Vollenweider and Lars Lind and Johan G. Eriksson and Karl Michaëlsson and Olli T. Raitakari and Sara Hägg and Nancy L. Pedersen and Karl-Heinz Herzig and Marjo-Riitta Järvelin and Juha Veijola and Mika Kivimaki and Rolf Jorde and Hermann Brenner and Meena Kumari and Chris Power and David J. Llewellyn and Elina Hyppönen},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5643555/},
year = {2017},
date = {2017-10-16},
journal = {Scientific Reports},
abstract = {The causal nature of the association between hypovitaminosis D and poor cognitive function in mid- to later-life is uncertain. Using a Mendelian randomisation(MR) approach, we examined the causal relationship between 25(OH)D and cognitive function. Data came from 172,349 participants from 17 cohorts. DHCR7(rs12785878), CYP2R1 rs12794714) and their combined synthesis score were chosen to proxy 25(OH)D. Cognitive tests were standardised into global and memory scores. Analyses were stratified by 25(OH)D tertiles, sex and age. Random effects meta-analyses assessed associations between 25(OH)D and cognitive function. Associations of serum 25(OH)D with global and memory-related cognitive function were non-linear (lower cognitive scores for both low and high 25(OH)D, p curvature ≤ 0.006), with much of the curvature attributed to a single study. DHCR7, CYP2R1, and the synthesis score were associated with small reductions in 25(OH)D per vitamin D-decreasing allele. However, coefficients for associations with global or memory-related cognitive function were non-significant and in opposing directions for DHCR7 and CYP2R1, with no overall association observed for the synthesis score. Coefficients for the synthesis score and global and memory cognition were similar when stratified by 25(OH)D tertiles, sex and age. We found no evidence for serum 25(OH)D concentration as a causal factor for cognitive performance in mid- to later life.},
keywords = {Cognitive Function, genetics, vitamin D},
pubstate = {published},
tppubtype = {article}
}

The causal nature of the association between hypovitaminosis D and poor cognitive function in mid- to later-life is uncertain. Using a Mendelian randomisation(MR) approach, we examined the causal relationship between 25(OH)D and cognitive function. Data came from 172,349 participants from 17 cohorts. DHCR7(rs12785878), CYP2R1 rs12794714) and their combined synthesis score were chosen to proxy 25(OH)D. Cognitive tests were standardised into global and memory scores. Analyses were stratified by 25(OH)D tertiles, sex and age. Random effects meta-analyses assessed associations between 25(OH)D and cognitive function. Associations of serum 25(OH)D with global and memory-related cognitive function were non-linear (lower cognitive scores for both low and high 25(OH)D, p curvature ≤ 0.006), with much of the curvature attributed to a single study. DHCR7, CYP2R1, and the synthesis score were associated with small reductions in 25(OH)D per vitamin D-decreasing allele. However, coefficients for associations with global or memory-related cognitive function were non-significant and in opposing directions for DHCR7 and CYP2R1, with no overall association observed for the synthesis score. Coefficients for the synthesis score and global and memory cognition were similar when stratified by 25(OH)D tertiles, sex and age. We found no evidence for serum 25(OH)D concentration as a causal factor for cognitive performance in mid- to later life.

Methods and Results—Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (P<5×10−8) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant.

Methods and Results—Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (P<5×10−8) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant.

Conclusions—We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.

Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents’ survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan.

Elevated blood pressure (BP) is a major global risk factor for cardiovascular disease. Genome-wide association studies have identified several genetic variants at the NPR3 locus associated with BP, but the functional impact of these variants remains to be determined. Here we confirmed, by a genome-wide association study within UK Biobank, the existence of two independent BP-related signals within NPR3 locus. Using human primary vascular smooth muscle cells and endothelial cells from different individuals, we found that the BP-elevating alleles within one linkage disequilibrium block identified by the sentinel variant rs1173771 was associated with lower endogenous NPR3 mRNA and protein levels in vascular smooth muscle cells, together with reduced levels in open chromatin and nuclear protein binding. The BP-elevating alleles also increased vascular smooth muscle cell proliferation, angiotensin II-induced calcium flux, and cell contraction. However, an analogous genotype-dependent association was not observed in vascular endothelial cells. Our study identifies novel, putative mechanisms for BP-associated variants at the NPR3 locus to elevate BP, further strengthening the case for targeting NPR-C as a therapeutic approach for hypertension and cardiovascular disease prevention.

To describe the active commuting (AC) patterns of adults with type 2 diabetes and how these relate to physical activity and sedentary behaviour in UK Biobank. Social and environmental correlates of AC will also be explored.
DESIGN:

Cross-sectional analysis of a cohort study.
SETTINGS:

This is a population cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 37 and 73 years were recruited between 2006 and 2010.
PARTICIPANTS:

6896 participants with a self-reported type 2 diabetes diagnosis who reported commuting to work and had complete covariate data were included in the analysis.
EXPOSURE MEASURES:

Outcome measures were weekly minutes of moderate to vigorous physical activity (MVPA), hours/day of sedentary time and participation in active travel.
RESULTS:

AC (reporting walking or cycling to work only) was reported by 5.5% of participants, with the great majority using the car to commute (80%). AC was associated with an additional 73 (95% CI 10.8 to 134.9) and 105 (95% CI 41.7 to 167.2) weekly minutes of MVPA for men and women, respectively. AC was associated with reduced sedentary time (β -1.1, 95% CI -1.6 to -0.7 hours/day for men; and β -0.8, 95% CI -1.2 to -0.3 hours/day for women). Deprivation and distance from home to work were identified as correlates of AC behaviour.
CONCLUSIONS:

To describe the active commuting (AC) patterns of adults with type 2 diabetes and how these relate to physical activity and sedentary behaviour in UK Biobank. Social and environmental correlates of AC will also be explored.
DESIGN:

Cross-sectional analysis of a cohort study.
SETTINGS:

This is a population cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 37 and 73 years were recruited between 2006 and 2010.
PARTICIPANTS:

6896 participants with a self-reported type 2 diabetes diagnosis who reported commuting to work and had complete covariate data were included in the analysis.
EXPOSURE MEASURES:

Outcome measures were weekly minutes of moderate to vigorous physical activity (MVPA), hours/day of sedentary time and participation in active travel.
RESULTS:

AC (reporting walking or cycling to work only) was reported by 5.5% of participants, with the great majority using the car to commute (80%). AC was associated with an additional 73 (95% CI 10.8 to 134.9) and 105 (95% CI 41.7 to 167.2) weekly minutes of MVPA for men and women, respectively. AC was associated with reduced sedentary time (β -1.1, 95% CI -1.6 to -0.7 hours/day for men; and β -0.8, 95% CI -1.2 to -0.3 hours/day for women). Deprivation and distance from home to work were identified as correlates of AC behaviour.
CONCLUSIONS:

Rates of AC are very low in adults with type 2 diabetes. However, AC offers a potentially sustainable solution to increasing physical activity and reducing sedentary behaviour. Therefore, strategies to improve the environment and encourage AC may help to increase population levels of physical activity and reduce the disease burden associated with type 2 diabetes.

Epidemiological cohorts typically contain a diverse set of phenotypes such that automation of phenome scans is non-trivial, because they require highly heterogeneous models. For this reason, phenome scans have to date tended to use a smaller homogeneous set of phenotypes that can be analysed in a consistent fashion. We present PHESANT (PHEnome Scan ANalysis Tool), a software package for performing comprehensive phenome scans in UK Biobank.
General features

PHESANT tests the association of a specified trait with all continuous, integer and categorical variables in UK Biobank, or a specified subset. PHESANT uses a novel rule-based algorithm to determine how to appropriately test each trait, then performs the analyses and produces plots and summary tables.
Implementation

Epidemiological cohorts typically contain a diverse set of phenotypes such that automation of phenome scans is non-trivial, because they require highly heterogeneous models. For this reason, phenome scans have to date tended to use a smaller homogeneous set of phenotypes that can be analysed in a consistent fashion. We present PHESANT (PHEnome Scan ANalysis Tool), a software package for performing comprehensive phenome scans in UK Biobank.
General features

PHESANT tests the association of a specified trait with all continuous, integer and categorical variables in UK Biobank, or a specified subset. PHESANT uses a novel rule-based algorithm to determine how to appropriately test each trait, then performs the analyses and produces plots and summary tables.
Implementation

@article{Benner2017,
title = {Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies},
author = {Christian Benner and Aki S.Havulinna and Marjo-RiittaJärvelin and VeikkoSalomaa and Samuli Ripatti and MattiPirinen },
url = {http://www.sciencedirect.com/science/article/pii/S0002929717303348},
year = {2017},
date = {2017-10-05},
journal = {American Journal of Human Genetics},
abstract = {During the past few years, various novel statistical methods have been developed for fine-mapping with the use of summary statistics from genome-wide association studies (GWASs). Although these approaches require information about the linkage disequilibrium (LD) between variants, there has not been a comprehensive evaluation of how estimation of the LD structure from reference genotype panels performs in comparison with that from the original individual-level GWAS data. Using population genotype data from Finland and the UK Biobank, we show here that a reference panel of 1,000 individuals from the target population is adequate for a GWAS cohort of up to 10,000 individuals, whereas smaller panels, such as those from the 1000 Genomes Project, should be avoided. We also show, both theoretically and empirically, that the size of the reference panel needs to scale with the GWAS sample size; this has important consequences for the application of these methods in ongoing GWAS meta-analyses and large biobank studies. We conclude by providing software tools and by recommending practices for sharing LD information to more efficiently exploit summary statistics in genetics research.},
keywords = {22627, GWAS, mapping, methodology, traits},
pubstate = {published},
tppubtype = {article}
}

During the past few years, various novel statistical methods have been developed for fine-mapping with the use of summary statistics from genome-wide association studies (GWASs). Although these approaches require information about the linkage disequilibrium (LD) between variants, there has not been a comprehensive evaluation of how estimation of the LD structure from reference genotype panels performs in comparison with that from the original individual-level GWAS data. Using population genotype data from Finland and the UK Biobank, we show here that a reference panel of 1,000 individuals from the target population is adequate for a GWAS cohort of up to 10,000 individuals, whereas smaller panels, such as those from the 1000 Genomes Project, should be avoided. We also show, both theoretically and empirically, that the size of the reference panel needs to scale with the GWAS sample size; this has important consequences for the application of these methods in ongoing GWAS meta-analyses and large biobank studies. We conclude by providing software tools and by recommending practices for sharing LD information to more efficiently exploit summary statistics in genetics research.

@article{Dannemann2017,
title = {The Contribution of Neanderthals to Phenotypic Variation in Modern Humans},
author = {Michael Dannemann and Janet Kelso},
url = {http://www.sciencedirect.com/science/article/pii/S0002929717303798},
year = {2017},
date = {2017-10-05},
journal = {American Journal of Human Genetics},
abstract = {Assessing the genetic contribution of Neanderthals to non-disease phenotypes in modern humans has been difficult because of the absence of large cohorts for which common phenotype information is available. Using baseline phenotypes collected for 112,000 individuals by the UK Biobank, we can now elaborate on previous findings that identified associations between signatures of positive selection on Neanderthal DNA and various modern human traits but not any specific phenotypic consequences. Here, we show that Neanderthal DNA affects skin tone and hair color, height, sleeping patterns, mood, and smoking status in present-day Europeans. Interestingly, multiple Neanderthal alleles at different loci contribute to skin and hair color in present-day Europeans, and these Neanderthal alleles contribute to both lighter and darker skin tones and hair color, suggesting that Neanderthals themselves were most likely variable in these traits.},
keywords = {12408, genetics, neanderthal},
pubstate = {published},
tppubtype = {article}
}

Assessing the genetic contribution of Neanderthals to non-disease phenotypes in modern humans has been difficult because of the absence of large cohorts for which common phenotype information is available. Using baseline phenotypes collected for 112,000 individuals by the UK Biobank, we can now elaborate on previous findings that identified associations between signatures of positive selection on Neanderthal DNA and various modern human traits but not any specific phenotypic consequences. Here, we show that Neanderthal DNA affects skin tone and hair color, height, sleeping patterns, mood, and smoking status in present-day Europeans. Interestingly, multiple Neanderthal alleles at different loci contribute to skin and hair color in present-day Europeans, and these Neanderthal alleles contribute to both lighter and darker skin tones and hair color, suggesting that Neanderthals themselves were most likely variable in these traits.

@article{Emdin2017b,
title = {Phenotypic Consequences of a Genetic Predisposition to Enhanced Nitric Oxide Signaling},
author = {Connor A. Emdin and Amit V. Khera and Derek Klarin and Pradeep Natarajan and Seyedeh M. Zekavat and Akihiro Nomura and Mary E. Haas and Krishna Aragam and Diego Ardissino and James G. Wilson and Heribert Schunkert and Ruth McPherson and Hugh Watkins and Roberto Elosua and Matthew J. Bown and Nilesh J. Samani and Usman Baber and Jeanette Erdmann and Padhraig Gormley and Aarno Palotie and Nathan Stitziel and Namrata Gupta and John N. Danesh and Danish Saleheen and Stacey B. Gabriel and Sekar Kathiresan},
url = {http://circ.ahajournals.org/content/early/2017/10/04/CIRCULATIONAHA.117.028021?utm_content=buffer79393&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer},
year = {2017},
date = {2017-10-05},
journal = {circulation},
abstract = {Background—Nitric oxide signaling plays a key role in regulation of vascular tone and platelet activation. Here, we seek to understand the impact of a genetic predisposition to enhanced nitric oxide signaling on risk for cardiovascular diseases, thus informing the potential utility of pharmacologic stimulation of the nitric oxide pathway as a therapeutic strategy.

Methods—We analyzed the association of common and rare genetic variants in two genes that mediate nitric oxide signaling [Nitric Oxide Synthase 3 (NOS3) and Guanylate Cyclase 1, Soluble, Alpha 3 (GUCY1A3)] with a range of human phenotypes. We selected two common variants (rs3918226 in NOS3 and rs7692387 in GUCY1A3) known to associate with increased NOS3 and GUCY1A3 expression and reduced mean arterial pressure, combined them into a genetic score, and standardized this exposure to a 5 mm Hg reduction in mean arterial pressure. Using individual-level data from 335,464 participants in the UK Biobank and summary association results from seven large-scale genome wide association studies, we examined the effect of this nitric oxide signaling score on cardiometabolic and other diseases. We also examined whether rare loss-of-function mutations in NOS3 and GUCY1A3 were associated with coronary heart disease using gene sequencing data from the Myocardial Infarction Genetics Consortium (n=27,815).

Background—Nitric oxide signaling plays a key role in regulation of vascular tone and platelet activation. Here, we seek to understand the impact of a genetic predisposition to enhanced nitric oxide signaling on risk for cardiovascular diseases, thus informing the potential utility of pharmacologic stimulation of the nitric oxide pathway as a therapeutic strategy.

Methods—We analyzed the association of common and rare genetic variants in two genes that mediate nitric oxide signaling [Nitric Oxide Synthase 3 (NOS3) and Guanylate Cyclase 1, Soluble, Alpha 3 (GUCY1A3)] with a range of human phenotypes. We selected two common variants (rs3918226 in NOS3 and rs7692387 in GUCY1A3) known to associate with increased NOS3 and GUCY1A3 expression and reduced mean arterial pressure, combined them into a genetic score, and standardized this exposure to a 5 mm Hg reduction in mean arterial pressure. Using individual-level data from 335,464 participants in the UK Biobank and summary association results from seven large-scale genome wide association studies, we examined the effect of this nitric oxide signaling score on cardiometabolic and other diseases. We also examined whether rare loss-of-function mutations in NOS3 and GUCY1A3 were associated with coronary heart disease using gene sequencing data from the Myocardial Infarction Genetics Consortium (n=27,815).

Machine-learning techniques have helped solve a broad range of prediction problems, yet are not widely used to build polygenic risk scores for the prediction of complex traits. We propose a novel heuristic based on machine-learning techniques (GraBLD) to boost the predictive performance of polygenic risk scores. Gradient boosted regression trees were first used to optimize the weights of SNPs included in the score, followed by a novel regional adjustment for linkage disequilibrium. A calibration set with sample size of ~200 individuals was sufficient for optimal performance. GraBLD yielded prediction R 2 of 0.239 and 0.082 using GIANT summary association statistics for height and BMI in the UK Biobank study (N = 130 K; 1.98 M SNPs), explaining 46.9% and 32.7% of the overall polygenic variance, respectively. For diabetes status, the area under the receiver operating characteristic curve was 0.602 in the UK Biobank study using summary-level association statistics from the DIAGRAM consortium. GraBLD outperformed other polygenic score heuristics for the prediction of height (p < 2.2 × 10-16) and BMI (p < 1.57 × 10-4), and was equivalent to LDpred for diabetes. Results were independently validated in the Health and Retirement Study (N = 8,292; 688,398 SNPs). Our report demonstrates the use of machine-learning techniques, coupled with summary-level data from large genome-wide meta-analyses to improve the prediction of polygenic traits.

The UK Biobank is a large-scale population-based study utilising cardiovascular magnetic resonance (CMR) to generate measurements of atrial and ventricular structure and function. This study aimed to quantify the association between modifiable cardiovascular risk factors and cardiac morphology and function in individuals without known cardiovascular disease.
Methods

Modifiable risk factors are associated with subclinical alterations in structure and function in all four cardiac chambers. BMI and systolic blood pressure are the most important modifiable risk factors affecting CMR parameters known to be linked to adverse outcomes.

RESEARCH DESIGN AND METHODS We undertook a prospective, general population cohort study by using UK Biobank. Cox proportional hazards models were used to explore the associations between both grip strength and diabetes and the outcomes of all-cause mortality and CVD incidence/mortality as well as to test for interactions between diabetes and grip strength.

RESULTS 347,130 UK Biobank participants with full data available (mean age 55.9 years, BMI 27.2 kg/m2, 54.2% women) were included in the analysis, of which 13,373 (4.0%) had diabetes. Over a median follow-up of 4.9 years (range 3.3–7.8 years), 6,209 died (594 as a result of CVD), and 4,301 developed CVD. Participants with diabetes were at higher risk of all-cause and CVD mortality and CVD incidence. Significant interactions (P < 0.05) existed whereby the risk of CVD mortality was higher in participants with diabetes with low (hazard ratio [HR] 4.05 [95% CI 2.72, 5.80]) versus high (HR 1.46 [0.87, 2.46]) grip strength. Similar results were observed for all-cause mortality and CVD incidence.

CONCLUSIONS Risk of adverse health outcomes among people with diabetes is lower in those with high grip strength. Low grip strength may be useful to identify a higher-risk subgroup of patients with diabetes. Intervention studies are required to determine whether resistance exercise can reduce risk.},
keywords = {diabetes, featured},
pubstate = {published},
tppubtype = {article}
}

OBJECTIVE Grip strength and diabetes are predictors of mortality and cardiovascular disease (CVD), but whether these risk factors interact to predispose to adverse health outcomes is unknown. This study determined the interactions between diabetes and grip strength and their association with health outcomes.

RESEARCH DESIGN AND METHODS We undertook a prospective, general population cohort study by using UK Biobank. Cox proportional hazards models were used to explore the associations between both grip strength and diabetes and the outcomes of all-cause mortality and CVD incidence/mortality as well as to test for interactions between diabetes and grip strength.

RESULTS 347,130 UK Biobank participants with full data available (mean age 55.9 years, BMI 27.2 kg/m2, 54.2% women) were included in the analysis, of which 13,373 (4.0%) had diabetes. Over a median follow-up of 4.9 years (range 3.3–7.8 years), 6,209 died (594 as a result of CVD), and 4,301 developed CVD. Participants with diabetes were at higher risk of all-cause and CVD mortality and CVD incidence. Significant interactions (P < 0.05) existed whereby the risk of CVD mortality was higher in participants with diabetes with low (hazard ratio [HR] 4.05 [95% CI 2.72, 5.80]) versus high (HR 1.46 [0.87, 2.46]) grip strength. Similar results were observed for all-cause mortality and CVD incidence.

CONCLUSIONS Risk of adverse health outcomes among people with diabetes is lower in those with high grip strength. Low grip strength may be useful to identify a higher-risk subgroup of patients with diabetes. Intervention studies are required to determine whether resistance exercise can reduce risk.

The relationship between insomnia symptoms and cognitive performance is unclear, particularly at the population level. We conducted the largest examination of this association to date through analysis of the UK Biobank, a large population-based sample of adults aged 40-69 years. We also sought to determine associations between cognitive performance and self-reported chronotype, sleep medication use and sleep duration.
METHODS:

Frequent insomnia symptoms were associated with cognitive impairment in unadjusted models; however, these effects were reversed after full adjustment, leaving those with frequent insomnia symptoms showing statistically better cognitive performance over those without. Relative to intermediate chronotype, evening chronotype was associated with superior task performance, while morning chronotype was associated with the poorest performance. Sleep medication use and both long (>9 h) and short (<7 h) sleep durations were associated with impaired performance.
CONCLUSIONS:

Our results suggest that after adjustment for potential confounding variables, frequent insomnia symptoms may be associated with a small statistical advantage, which is unlikely to be clinically meaningful, on simple neurocognitive tasks. Further work is required to examine the mechanistic underpinnings of an apparent evening chronotype advantage in cognitive performance and the impairment associated with morning chronotype, sleep medication use, and sleep duration extremes.},
keywords = {cognitive performance, sleep},
pubstate = {published},
tppubtype = {article}
}

The relationship between insomnia symptoms and cognitive performance is unclear, particularly at the population level. We conducted the largest examination of this association to date through analysis of the UK Biobank, a large population-based sample of adults aged 40-69 years. We also sought to determine associations between cognitive performance and self-reported chronotype, sleep medication use and sleep duration.
METHODS:

Frequent insomnia symptoms were associated with cognitive impairment in unadjusted models; however, these effects were reversed after full adjustment, leaving those with frequent insomnia symptoms showing statistically better cognitive performance over those without. Relative to intermediate chronotype, evening chronotype was associated with superior task performance, while morning chronotype was associated with the poorest performance. Sleep medication use and both long (>9 h) and short (<7 h) sleep durations were associated with impaired performance.
CONCLUSIONS:

Our results suggest that after adjustment for potential confounding variables, frequent insomnia symptoms may be associated with a small statistical advantage, which is unlikely to be clinically meaningful, on simple neurocognitive tasks. Further work is required to examine the mechanistic underpinnings of an apparent evening chronotype advantage in cognitive performance and the impairment associated with morning chronotype, sleep medication use, and sleep duration extremes.

@article{Doiron2017,
title = {Residential Air Pollution and Associations with Wheeze and Shortness of Breath in Adults: A Combined Analysis of Cross-Sectional Data from Two Large European Cohorts.},
author = {D Doiron and K de Hoogh and N Probst-Hensch and S Mbatchou and M Eeftens and Y Cai and C Schindler and I Fortier and S Hodgson and A Gaye and R Stolk and A Hansell },
url = {https://www.ncbi.nlm.nih.gov/pubmed/28963089},
year = {2017},
date = {2017-09-29},
journal = {Environmental health perspectives},
abstract = {Research examining associations between air pollution exposure and respiratory symptoms in adults has generally been inconclusive. This may be related in part to sample size issues, which also preclude analysis in potentially vulnerable subgroups.
OBJECTIVES:

We estimated associations between air pollution exposures and the prevalence of wheeze and shortness of breath using harmonized baseline data from two very large European cohorts, Lifelines (2006-2013) and UK Biobank (2006-2010). Our aim was also to determine whether the relationship between air pollution and respiratory symptom prevalence differed between individuals with different characteristics.
METHODS:

Cross-sectional analyses explored associations between prevalence of self-reported wheeze and shortness of breath and annual mean particulate matter with aerodynamic diameter <2.5μm, 2.5-10μm, and <10μm (PM2.5, PMcoarse, and PM10, respectively) and nitrogen dioxide (NO2) concentrations at place of residence using logistic regression. Subgroup analyses and tests for interaction were performed for age, sex, smoking status, household income, obesity status, and asthma status.
RESULTS:

All PM exposures were associated with respiratory symptoms based on single-pollutant models, with the largest associations seen for PM2.5 with prevalence of wheezing {odds ratio (OR)=1.16 per 5μg/m³ [95% confidence interval (CI): 1.11, 1.21]} and shortness of breath [OR=1.61 per 5μg/m³ (95% CI: 1.45, 1.78)]. The association between shortness of breath and a 5-μg/m³ increment in PM2.5 was significantly higher for individuals from lower-[OR=1.73 (95% CI: 1.52, 1.97)] versus higher-income households [OR=1.31 (95% CI: 1.11, 1.55); p-interaction=0.005), whereas the association between PM2.5 and wheeze was limited to lower-income participants [OR=1.30 (95% CI: 1.22, 1.38) vs. OR=1.02; (95% CI: 0.96, 1.08); p-interaction<0.001]. Exposure to NO2 also showed positive associations with wheeze and shortness of breath.
CONCLUSION:

Exposure to PM and NO2 air pollution was associated with the prevalence of wheeze and shortness of breath in this large study, with stronger associations between PM2.5 and both outcomes among lower- versus higher-income participants. https://doi.org/10.1289/EHP1353.},
keywords = {9946, air pollution, shortness of breath},
pubstate = {published},
tppubtype = {article}
}

Research examining associations between air pollution exposure and respiratory symptoms in adults has generally been inconclusive. This may be related in part to sample size issues, which also preclude analysis in potentially vulnerable subgroups.
OBJECTIVES:

We estimated associations between air pollution exposures and the prevalence of wheeze and shortness of breath using harmonized baseline data from two very large European cohorts, Lifelines (2006-2013) and UK Biobank (2006-2010). Our aim was also to determine whether the relationship between air pollution and respiratory symptom prevalence differed between individuals with different characteristics.
METHODS:

Cross-sectional analyses explored associations between prevalence of self-reported wheeze and shortness of breath and annual mean particulate matter with aerodynamic diameter <2.5μm, 2.5-10μm, and <10μm (PM2.5, PMcoarse, and PM10, respectively) and nitrogen dioxide (NO2) concentrations at place of residence using logistic regression. Subgroup analyses and tests for interaction were performed for age, sex, smoking status, household income, obesity status, and asthma status.
RESULTS:

All PM exposures were associated with respiratory symptoms based on single-pollutant models, with the largest associations seen for PM2.5 with prevalence of wheezing {odds ratio (OR)=1.16 per 5μg/m³ [95% confidence interval (CI): 1.11, 1.21]} and shortness of breath [OR=1.61 per 5μg/m³ (95% CI: 1.45, 1.78)]. The association between shortness of breath and a 5-μg/m³ increment in PM2.5 was significantly higher for individuals from lower-[OR=1.73 (95% CI: 1.52, 1.97)] versus higher-income households [OR=1.31 (95% CI: 1.11, 1.55); p-interaction=0.005), whereas the association between PM2.5 and wheeze was limited to lower-income participants [OR=1.30 (95% CI: 1.22, 1.38) vs. OR=1.02; (95% CI: 0.96, 1.08); p-interaction<0.001]. Exposure to NO2 also showed positive associations with wheeze and shortness of breath.
CONCLUSION:

Exposure to PM and NO2 air pollution was associated with the prevalence of wheeze and shortness of breath in this large study, with stronger associations between PM2.5 and both outcomes among lower- versus higher-income participants. https://doi.org/10.1289/EHP1353.

A large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%, <50 year olds, 28.4%). RDW was associated with 194 independent genetic signals; 71 are known for conditions including autoimmune disease, certain cancers, BMI, Alzheimer's disease, longevity, age at menopause, bone density, myositis, Parkinson's disease, and age-related macular degeneration. Exclusion of anemic participants did not affect the overall findings. Pathways analysis showed enrichment for telomere maintenance, ribosomal RNA, and apoptosis. The majority of RDW-associated signals were intronic (119 of 194), including SNP rs6602909 located in an intron of oncogene GAS6, an eQTL in whole blood.
CONCLUSIONS:

Although increased RDW is predictive of cardiovascular outcomes, this was not explained by known CVD or related lipid genetic risks, and a RDW genetic score was not predictive of incident disease. The predictive value of RDW for a range of negative health outcomes may in part be due to variants influencing fundamental pathways of aging.},
keywords = {14631, genetics, red blood cells},
pubstate = {published},
tppubtype = {article}
}

A large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%, <50 year olds, 28.4%). RDW was associated with 194 independent genetic signals; 71 are known for conditions including autoimmune disease, certain cancers, BMI, Alzheimer's disease, longevity, age at menopause, bone density, myositis, Parkinson's disease, and age-related macular degeneration. Exclusion of anemic participants did not affect the overall findings. Pathways analysis showed enrichment for telomere maintenance, ribosomal RNA, and apoptosis. The majority of RDW-associated signals were intronic (119 of 194), including SNP rs6602909 located in an intron of oncogene GAS6, an eQTL in whole blood.
CONCLUSIONS:

Although increased RDW is predictive of cardiovascular outcomes, this was not explained by known CVD or related lipid genetic risks, and a RDW genetic score was not predictive of incident disease. The predictive value of RDW for a range of negative health outcomes may in part be due to variants influencing fundamental pathways of aging.

Native T1-mapping provides quantitative myocardial tissue characterization for cardiovascular diseases (CVD), without the need for gadolinium. However, its translation into clinical practice is hindered by differences between techniques and the lack of established reference values. We provide typical myocardial T1-ranges for 18 commonly encountered CVDs using a single T1-mapping technique – Shortened Look-Locker Inversion Recovery (ShMOLLI), also used in the large UK Biobank and Hypertrophic Cardiomyopathy Registry study.

Methods

We analyzed 1291 subjects who underwent CMR (1.5-Tesla, MAGNETOM-Avanto, Siemens Healthcare, Erlangen, Germany) between 2009 and 2016, who had a single CVD diagnosis, with mid-ventricular T1-map assessment. A region of interest (ROI) was placed on native T1-maps in the “most-affected myocardium”, characterized by the presence of late gadolinium enhancement (LGE), or regional wall motion abnormalities (RWMA) on cines. Another ROI was placed in the “reference myocardium” as far as possible from LGE/RWMA, and in the septum if no focal abnormality was present. To further define normality, we included native T1 of healthy subjects from an existing dataset after sub-endocardial pixel-erosions.

Results

Native T1 of patients with normal CMR (938 ± 21 ms) was similar compared to healthy subjects (941 ± 23 ms). Across all patient groups (57 ± 19 yrs., 65% males), focally affected myocardium had significantly different T1 value compared to reference myocardium (all p < 0.001). In the affected myocardium, cardiac amyloidosis (1119 ± 61 ms) had the highest native T1 compared to normal and all other CVDs, while iron-overload (795 ± 58 ms) and Anderson-Fabry disease (863 ± 23 ms) had the lowest native reference T1 (all p < 0.001). Future studies designed to detect the large T1 differences between affected and reference myocardium are estimated to require small sample-sizes (n < 50). However, studies designed to detect the small T1 differences between reference myocardium in CVDs and healthy controls can require several thousand of subjects.

Conclusions

We provide typical T1-ranges for common clinical cardiac conditions in the largest cohort to-date, using ShMOLLI T1-mapping at 1.5 T. Sample-size calculations from this study may be useful for the design of future studies and trials that use T1-mapping as an endpoint.
},
keywords = {imaging},
pubstate = {published},
tppubtype = {article}
}

Native T1-mapping provides quantitative myocardial tissue characterization for cardiovascular diseases (CVD), without the need for gadolinium. However, its translation into clinical practice is hindered by differences between techniques and the lack of established reference values. We provide typical myocardial T1-ranges for 18 commonly encountered CVDs using a single T1-mapping technique – Shortened Look-Locker Inversion Recovery (ShMOLLI), also used in the large UK Biobank and Hypertrophic Cardiomyopathy Registry study.

Methods

We analyzed 1291 subjects who underwent CMR (1.5-Tesla, MAGNETOM-Avanto, Siemens Healthcare, Erlangen, Germany) between 2009 and 2016, who had a single CVD diagnosis, with mid-ventricular T1-map assessment. A region of interest (ROI) was placed on native T1-maps in the “most-affected myocardium”, characterized by the presence of late gadolinium enhancement (LGE), or regional wall motion abnormalities (RWMA) on cines. Another ROI was placed in the “reference myocardium” as far as possible from LGE/RWMA, and in the septum if no focal abnormality was present. To further define normality, we included native T1 of healthy subjects from an existing dataset after sub-endocardial pixel-erosions.

Results

Native T1 of patients with normal CMR (938 ± 21 ms) was similar compared to healthy subjects (941 ± 23 ms). Across all patient groups (57 ± 19 yrs., 65% males), focally affected myocardium had significantly different T1 value compared to reference myocardium (all p < 0.001). In the affected myocardium, cardiac amyloidosis (1119 ± 61 ms) had the highest native T1 compared to normal and all other CVDs, while iron-overload (795 ± 58 ms) and Anderson-Fabry disease (863 ± 23 ms) had the lowest native reference T1 (all p < 0.001). Future studies designed to detect the large T1 differences between affected and reference myocardium are estimated to require small sample-sizes (n < 50). However, studies designed to detect the small T1 differences between reference myocardium in CVDs and healthy controls can require several thousand of subjects.

Conclusions

We provide typical T1-ranges for common clinical cardiac conditions in the largest cohort to-date, using ShMOLLI T1-mapping at 1.5 T. Sample-size calculations from this study may be useful for the design of future studies and trials that use T1-mapping as an endpoint.

The Trail Making Test (TMT) is a widely used test of executive function and has been thought to be strongly associated with general cognitive function. We examined the genetic architecture of the TMT and its shared genetic aetiology with other tests of cognitive function in 23 821 participants from UK Biobank. The single-nucleotide polymorphism-based heritability estimates for trail-making measures were 7.9% (part A), 22.4% (part B) and 17.6% (part B-part A). Significant genetic correlations were identified between trail-making measures and verbal-numerical reasoning (rg>0.6), general cognitive function (rg>0.6), processing speed (rg>0.7) and memory (rg>0.3). Polygenic profile analysis indicated considerable shared genetic aetiology between trail making, general cognitive function, processing speed and memory (standardized β between 0.03 and 0.08). These results suggest that trail making is both phenotypically and genetically strongly associated with general cognitive function and processing speed.

@article{Perez-Cornago2017,
title = {Prospective investigation of risk factors for prostate cancer in the UK Biobank cohort study},
author = {Aurora Perez-Cornago and Timothy J Key and Naomi E Allen and Georgina K Fensom and Kathryn E Bradbury and Richard Martin and Ruth Travis
},
url = {https://www.nature.com/bjc/journal/vaop/ncurrent/pdf/bjc2017312a.pdf?foxtrotcallback=true},
year = {2017},
date = {2017-09-15},
journal = {British Journal of Cancer},
abstract = {Background:
Prostate cancer is the most common cancer in British men but its aetiology is not well understood. We aimed to
identify risk factors for prostate cancer in British males.

Methods:
We studied 219 335 men from the UK Biobank study who were free from cancer at baseline. Exposure data were
collected at recruitment. Prostate cancer risk by the different exposures was estimated using multivariable-adjusted Cox
proportional hazards models.

Background:
Prostate cancer is the most common cancer in British men but its aetiology is not well understood. We aimed to
identify risk factors for prostate cancer in British males.

Methods:
We studied 219 335 men from the UK Biobank study who were free from cancer at baseline. Exposure data were
collected at recruitment. Prostate cancer risk by the different exposures was estimated using multivariable-adjusted Cox
proportional hazards models.

Conclusions:
In this new large British prospective study, we identified associations with already-established, putative and possible
novel risk factors for being diagnosed with prostate cancer. Future research will examine associations by tumour characteristics.

@article{Welikala2017,
title = {Automated arteriole and venule classification using deep learning for retinal images from the UK Biobank cohort.},
author = {RA Welikala and P Foster and PH Whincup and AR Rudnicka and CG Owen and DP Strachan and SA Barman and UK Biobank Eye and Vision Consortium.},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28917120},
year = {2017},
date = {2017-09-08},
journal = {Computers in Biology and Medicine},
abstract = {The morphometric characteristics of the retinal vasculature are associated with future risk of many systemic and vascular diseases. However, analysis of data from large population based studies is needed to help resolve uncertainties in some of these associations. This requires automated systems that extract quantitative measures of vessel morphology from large numbers of retinal images. Associations between retinal vessel morphology and disease precursors/outcomes may be similar or opposing for arterioles and venules. Therefore, the accurate detection of the vessel type is an important element in such automated systems. This paper presents a deep learning approach for the automatic classification of arterioles and venules across the entire retinal image, including vessels located at the optic disc. This comprises of a convolutional neural network whose architecture contains six learned layers: three convolutional and three fully-connected. Complex patterns are automatically learnt from the data, which avoids the use of hand crafted features. The method is developed and evaluated using 835,914 centreline pixels derived from 100 retinal images selected from the 135,867 retinal images obtained at the UK Biobank (large population-based cohort study of middle aged and older adults) baseline examination. This is a challenging dataset in respect to image quality and hence arteriole/venule classification is required to be highly robust. The method achieves a significant increase in accuracy of 8.1% when compared to the baseline method, resulting in an arteriole/venule classification accuracy of 86.97% (per pixel basis) over the entire retinal image.},
keywords = {computer, imaging, methodology, Retinal, vision},
pubstate = {published},
tppubtype = {article}
}

The morphometric characteristics of the retinal vasculature are associated with future risk of many systemic and vascular diseases. However, analysis of data from large population based studies is needed to help resolve uncertainties in some of these associations. This requires automated systems that extract quantitative measures of vessel morphology from large numbers of retinal images. Associations between retinal vessel morphology and disease precursors/outcomes may be similar or opposing for arterioles and venules. Therefore, the accurate detection of the vessel type is an important element in such automated systems. This paper presents a deep learning approach for the automatic classification of arterioles and venules across the entire retinal image, including vessels located at the optic disc. This comprises of a convolutional neural network whose architecture contains six learned layers: three convolutional and three fully-connected. Complex patterns are automatically learnt from the data, which avoids the use of hand crafted features. The method is developed and evaluated using 835,914 centreline pixels derived from 100 retinal images selected from the 135,867 retinal images obtained at the UK Biobank (large population-based cohort study of middle aged and older adults) baseline examination. This is a challenging dataset in respect to image quality and hence arteriole/venule classification is required to be highly robust. The method achieves a significant increase in accuracy of 8.1% when compared to the baseline method, resulting in an arteriole/venule classification accuracy of 86.97% (per pixel basis) over the entire retinal image.

@article{Mostafavi2017,
title = {Identifying genetic variants that affect viability in large cohorts},
author = {Hakhamanesh Mostafavi and Tomaz Berisa and Felix R. Day and John R. B. Perry and Molly Przeworski and Joseph K. Pickrell
},
url = {http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2002458},
year = {2017},
date = {2017-09-05},
journal = {PLoS Biology },
abstract = {A number of open questions in human evolutionary genetics would become tractable if we were able to directly measure evolutionary fitness. As a step towards this goal, we developed a method to examine whether individual genetic variants, or sets of genetic variants, currently influence viability. The approach consists in testing whether the frequency of an allele varies across ages, accounting for variation in ancestry. We applied it to the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort and to the parents of participants in the UK Biobank. Across the genome, we found only a few common variants with large effects on age-specific mortality: tagging the APOE ε4 allele and near CHRNA3. These results suggest that when large, even late-onset effects are kept at low frequency by purifying selection. Testing viability effects of sets of genetic variants that jointly influence 1 of 42 traits, we detected a number of strong signals. In participants of the UK Biobank of British ancestry, we found that variants that delay puberty timing are associated with a longer parental life span (P~6.2 × 10−6 for fathers and P~2.0 × 10−3 for mothers), consistent with epidemiological studies. Similarly, variants associated with later age at first birth are associated with a longer maternal life span (P~1.4 × 10−3). Signals are also observed for variants influencing cholesterol levels, risk of coronary artery disease (CAD), body mass index, as well as risk of asthma. These signals exhibit consistent effects in the GERA cohort and among participants of the UK Biobank of non-British ancestry. We also found marked differences between males and females, most notably at the CHRNA3 locus, and variants associated with risk of CAD and cholesterol levels. Beyond our findings, the analysis serves as a proof of principle for how upcoming biomedical data sets can be used to learn about selection effects in contemporary humans.},
keywords = {evolutionary fitness, genetics},
pubstate = {published},
tppubtype = {article}
}

A number of open questions in human evolutionary genetics would become tractable if we were able to directly measure evolutionary fitness. As a step towards this goal, we developed a method to examine whether individual genetic variants, or sets of genetic variants, currently influence viability. The approach consists in testing whether the frequency of an allele varies across ages, accounting for variation in ancestry. We applied it to the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort and to the parents of participants in the UK Biobank. Across the genome, we found only a few common variants with large effects on age-specific mortality: tagging the APOE ε4 allele and near CHRNA3. These results suggest that when large, even late-onset effects are kept at low frequency by purifying selection. Testing viability effects of sets of genetic variants that jointly influence 1 of 42 traits, we detected a number of strong signals. In participants of the UK Biobank of British ancestry, we found that variants that delay puberty timing are associated with a longer parental life span (P~6.2 × 10−6 for fathers and P~2.0 × 10−3 for mothers), consistent with epidemiological studies. Similarly, variants associated with later age at first birth are associated with a longer maternal life span (P~1.4 × 10−3). Signals are also observed for variants influencing cholesterol levels, risk of coronary artery disease (CAD), body mass index, as well as risk of asthma. These signals exhibit consistent effects in the GERA cohort and among participants of the UK Biobank of non-British ancestry. We also found marked differences between males and females, most notably at the CHRNA3 locus, and variants associated with risk of CAD and cholesterol levels. Beyond our findings, the analysis serves as a proof of principle for how upcoming biomedical data sets can be used to learn about selection effects in contemporary humans.

@article{Orini2017,
title = {Long-term intra-individual reproducibility of heart rate dynamics during exercise and recovery in the UK Biobank cohort},
author = {M Orini and A Tinker and PB Munroe and PD Lambiase},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28873397},
year = {2017},
date = {2017-09-05},
journal = {PLoS One},
abstract = {The heart rate (HR) response to exercise provides useful information about the autonomic function and has prognostic value, but its reproducibility over a long period of time, a critical requirement for using it as a clinical biomarker, is undetermined.

AIM:

To determine the intra-individual reproducibility of HR dynamics during sub-maximum exercise and one minute recovery.

821 individuals complied with inclusion criteria for reproducibility analysis, including peak workload differences between assessments ≤10 W. Intra-individual correlation between HR profile during the first and the second assessment was very high and higher than inter-individual correlation (0.92±0.08 vs 0.87±0.11, p<0.01). Intra-individual correlation of indices describing HR dynamics was: ρ = 0.81 for maximum HR during exercise; ρ = 0.71 for minimum HR during recovery; ρ = 0.70 for HR changes during both exercise and recovery; Intra-individual correlation was higher for these indices of HR dynamics than for resting HR (ρ = 0.64). Bland-Altman plots demonstrated good agreement between HR indices estimated during the first and second assessment. A small but consistent bias was registered for all repeated measurements. The intra-individual consistency of abnormal values was about 60-70%.

CONCLUSIONS:

The HR dynamics during exercise and recovery are reproducible over a period of 3 years, with moderate to strong intra-individual reproducibility of abnormal values.},
keywords = {exercise, heart rate},
pubstate = {published},
tppubtype = {article}
}

The heart rate (HR) response to exercise provides useful information about the autonomic function and has prognostic value, but its reproducibility over a long period of time, a critical requirement for using it as a clinical biomarker, is undetermined.

AIM:

To determine the intra-individual reproducibility of HR dynamics during sub-maximum exercise and one minute recovery.

821 individuals complied with inclusion criteria for reproducibility analysis, including peak workload differences between assessments ≤10 W. Intra-individual correlation between HR profile during the first and the second assessment was very high and higher than inter-individual correlation (0.92±0.08 vs 0.87±0.11, p<0.01). Intra-individual correlation of indices describing HR dynamics was: ρ = 0.81 for maximum HR during exercise; ρ = 0.71 for minimum HR during recovery; ρ = 0.70 for HR changes during both exercise and recovery; Intra-individual correlation was higher for these indices of HR dynamics than for resting HR (ρ = 0.64). Bland-Altman plots demonstrated good agreement between HR indices estimated during the first and second assessment. A small but consistent bias was registered for all repeated measurements. The intra-individual consistency of abnormal values was about 60-70%.

CONCLUSIONS:

The HR dynamics during exercise and recovery are reproducible over a period of 3 years, with moderate to strong intra-individual reproducibility of abnormal values.

@article{Rask-Andersen2017,
title = {Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status.},
author = {M Rask-Andersen and T Karlsson and WE Ek and A Johansson},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28873402},
year = {2017},
date = {2017-09-05},
journal = {PLOS Genetics},
abstract = {Previous genome-wide association studies (GWAS) have identified hundreds of genetic loci to be associated with body mass index (BMI) and risk of obesity. Genetic effects can differ between individuals depending on lifestyle or environmental factors due to gene-environment interactions. In this study, we examine gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource. A total of 94 BMI-associated SNPs, selected from a previous GWAS on BMI, were used to construct weighted genetic scores for BMI (GSBMI). Linear regression modeling was used to estimate the effect of gene-environment interactions on BMI for 131 lifestyle factors related to: dietary habits, smoking and alcohol consumption, physical activity, socioeconomic status, mental health, sleeping patterns, as well as female-specific factors such as menopause and childbirth. In total, 15 lifestyle factors were observed to interact with GSBMI, of which alcohol intake frequency, usual walking pace, and Townsend deprivation index, a measure of socioeconomic status, were all highly significant (p = 1.45*10-29, p = 3.83*10-26, p = 4.66*10-11, respectively). Interestingly, the frequency of alcohol consumption, rather than the total weekly amount resulted in a significant interaction. The FTO locus was the strongest single locus interacting with any of the lifestyle factors. However, 13 significant interactions were also observed after omitting the FTO locus from the genetic score. Our analyses indicate that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score. However, the underlying causal mechanisms of gene-environmental interactions are difficult to deduce from cross-sectional data alone and controlled experiments are required to fully characterise the causal factors.},
keywords = {alcohol, genetics, physical activity},
pubstate = {published},
tppubtype = {article}
}

Previous genome-wide association studies (GWAS) have identified hundreds of genetic loci to be associated with body mass index (BMI) and risk of obesity. Genetic effects can differ between individuals depending on lifestyle or environmental factors due to gene-environment interactions. In this study, we examine gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource. A total of 94 BMI-associated SNPs, selected from a previous GWAS on BMI, were used to construct weighted genetic scores for BMI (GSBMI). Linear regression modeling was used to estimate the effect of gene-environment interactions on BMI for 131 lifestyle factors related to: dietary habits, smoking and alcohol consumption, physical activity, socioeconomic status, mental health, sleeping patterns, as well as female-specific factors such as menopause and childbirth. In total, 15 lifestyle factors were observed to interact with GSBMI, of which alcohol intake frequency, usual walking pace, and Townsend deprivation index, a measure of socioeconomic status, were all highly significant (p = 1.45*10-29, p = 3.83*10-26, p = 4.66*10-11, respectively). Interestingly, the frequency of alcohol consumption, rather than the total weekly amount resulted in a significant interaction. The FTO locus was the strongest single locus interacting with any of the lifestyle factors. However, 13 significant interactions were also observed after omitting the FTO locus from the genetic score. Our analyses indicate that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score. However, the underlying causal mechanisms of gene-environmental interactions are difficult to deduce from cross-sectional data alone and controlled experiments are required to fully characterise the causal factors.

The heart rate (HR) response to exercise provides useful information about the autonomic function and has prognostic value, but its reproducibility over a long period of time, a critical requirement for using it as a clinical biomarker, is undetermined.

Aim

To determine the intra-individual reproducibility of HR dynamics during sub-maximum exercise and one minute recovery.

821 individuals complied with inclusion criteria for reproducibility analysis, including peak workload differences between assessments ≤10 W. Intra-individual correlation between HR profile during the first and the second assessment was very high and higher than inter-individual correlation (0.92±0.08 vs 0.87±0.11, p<0.01). Intra-individual correlation of indices describing HR dynamics was: ρ = 0.81 for maximum HR during exercise; ρ = 0.71 for minimum HR during recovery; ρ = 0.70 for HR changes during both exercise and recovery; Intra-individual correlation was higher for these indices of HR dynamics than for resting HR (ρ = 0.64). Bland-Altman plots demonstrated good agreement between HR indices estimated during the first and second assessment. A small but consistent bias was registered for all repeated measurements. The intra-individual consistency of abnormal values was about 60–70%.

Conclusions

The HR dynamics during exercise and recovery are reproducible over a period of 3 years, with moderate to strong intra-individual reproducibility of abnormal values.
},
keywords = {8256, heart rate},
pubstate = {published},
tppubtype = {article}
}

The heart rate (HR) response to exercise provides useful information about the autonomic function and has prognostic value, but its reproducibility over a long period of time, a critical requirement for using it as a clinical biomarker, is undetermined.

Aim

To determine the intra-individual reproducibility of HR dynamics during sub-maximum exercise and one minute recovery.

821 individuals complied with inclusion criteria for reproducibility analysis, including peak workload differences between assessments ≤10 W. Intra-individual correlation between HR profile during the first and the second assessment was very high and higher than inter-individual correlation (0.92±0.08 vs 0.87±0.11, p<0.01). Intra-individual correlation of indices describing HR dynamics was: ρ = 0.81 for maximum HR during exercise; ρ = 0.71 for minimum HR during recovery; ρ = 0.70 for HR changes during both exercise and recovery; Intra-individual correlation was higher for these indices of HR dynamics than for resting HR (ρ = 0.64). Bland-Altman plots demonstrated good agreement between HR indices estimated during the first and second assessment. A small but consistent bias was registered for all repeated measurements. The intra-individual consistency of abnormal values was about 60–70%.

Conclusions

The HR dynamics during exercise and recovery are reproducible over a period of 3 years, with moderate to strong intra-individual reproducibility of abnormal values.

@article{Sofer2017,
title = {Genome-Wide Association Study of Blood Pressure Traits by Hispanic/Latino Background: the Hispanic Community Health Study/Study of Latinos.},
author = {T Sofer and Q Wong and FP Hartwig and K Taylor and HR Warren and E Evangelou and CP Cabrera and D Levy and H Kramer and LA Lange and BL Horta and KF Kerr and AP Reiner and N Franceschini},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28871152},
year = {2017},
date = {2017-09-04},
journal = {Scientific Reports},
abstract = {Hypertension prevalence varies between ethnic groups, possibly due to differences in genetic, environmental, and cultural determinants. Hispanic/Latino Americans are a diverse and understudied population. We performed a genome-wide association study (GWAS) of blood pressure (BP) traits in 12,278 participants from the Hispanics Community Health Study/Study of Latinos (HCHS/SOL). In the discovery phase we identified eight previously unreported BP loci. In the replication stage, we tested these loci in the 1982 Pelotas Birth Cohort Study of admixed Southern Brazilians, the COGENT-BP study of African descent, women of European descent from the Women Health Initiative (WHI), and a sample of European descent from the UK Biobank. No loci met the Bonferroni-adjusted level of statistical significance (0.0024). Two loci had marginal evidence of replication: rs78701042 (NGF) with diastolic BP (P = 0.008 in the 1982 Pelotas Birth Cohort Study), and rs7315692 (SLC5A8) with systolic BP (P = 0.007 in European ancestry replication). We investigated whether previously reported loci associated with BP in studies of European, African, and Asian ancestry generalize to Hispanics/Latinos. Overall, 26% of the known associations in studies of individuals of European and Chinese ancestries generalized, while only a single association previously discovered in a people of African descent generalized.},
keywords = {genetics},
pubstate = {published},
tppubtype = {article}
}

Hypertension prevalence varies between ethnic groups, possibly due to differences in genetic, environmental, and cultural determinants. Hispanic/Latino Americans are a diverse and understudied population. We performed a genome-wide association study (GWAS) of blood pressure (BP) traits in 12,278 participants from the Hispanics Community Health Study/Study of Latinos (HCHS/SOL). In the discovery phase we identified eight previously unreported BP loci. In the replication stage, we tested these loci in the 1982 Pelotas Birth Cohort Study of admixed Southern Brazilians, the COGENT-BP study of African descent, women of European descent from the Women Health Initiative (WHI), and a sample of European descent from the UK Biobank. No loci met the Bonferroni-adjusted level of statistical significance (0.0024). Two loci had marginal evidence of replication: rs78701042 (NGF) with diastolic BP (P = 0.008 in the 1982 Pelotas Birth Cohort Study), and rs7315692 (SLC5A8) with systolic BP (P = 0.007 in European ancestry replication). We investigated whether previously reported loci associated with BP in studies of European, African, and Asian ancestry generalize to Hispanics/Latinos. Overall, 26% of the known associations in studies of individuals of European and Chinese ancestries generalized, while only a single association previously discovered in a people of African descent generalized.

Osteoporosis is a common disease diagnosed primarily by measurement of bone mineral density (BMD). We undertook a genome-wide association study (GWAS) in 142,487 individuals from the UK Biobank to identify loci associated with BMD as estimated by quantitative ultrasound of the heel. We identified 307 conditionally independent single-nucleotide polymorphisms (SNPs) that attained genome-wide significance at 203 loci, explaining approximately 12% of the phenotypic variance. These included 153 previously unreported loci, and several rare variants with large effect sizes. To investigate the underlying mechanisms, we undertook (1) bioinformatic, functional genomic annotation and human osteoblast expression studies; (2) gene-function prediction; (3) skeletal phenotyping of 120 knockout mice with deletions of genes adjacent to lead independent SNPs; and (4) analysis of gene expression in mouse osteoblasts, osteocytes and osteoclasts. The results implicate GPC6 as a novel determinant of BMD, and also identify abnormal skeletal phenotypes in knockout mice associated with a further 100 prioritized genes.

@article{Doiron2017b,
title = {Residential Air Pollution and Associations with Wheeze and Shortness of Breath in Adults: A Combined Analysis of Cross-Sectional Data from Two Large European Cohorts},
author = {Dany Doiron and Kees de Hoogh and Nicole Probst-Hensch and Stéphane Mbatchou and Marloes Eeftens and Yutong Cai and Christian Schindler and Isabel Fortier and Susan Hodgson and Amadou Gaye and Ronald Stolk and Anna Hansell},
url = {https://ehp.niehs.nih.gov/ehp1353/},
year = {2017},
date = {2017-09-01},
journal = {Environmental health perspectives},
abstract = {Research examining associations between air pollution exposure and respiratory symptoms in adults has generally been inconclusive. This may be related in part to sample size issues, which also preclude analysis in potentially vulnerable subgroups.

Objectives:
We estimated associations between air pollution exposures and the prevalence of wheeze and shortness of breath using harmonized baseline data from two very large European cohorts, Lifelines (2006–2013) and UK Biobank (2006–2010). Our aim was also to determine whether the relationship between air pollution and respiratory symptom prevalence differed between individuals with different characteristics.

Conclusion:
Exposure to PM and NO2 air pollution was associated with the prevalence of wheeze and shortness of breath in this large study, with stronger associations between PM2.5 and both outcomes among lower- versus higher-income participants. https://doi.org/10.1289/EHP1353},
keywords = {9946, pollution, shortness of breath},
pubstate = {published},
tppubtype = {article}
}

Research examining associations between air pollution exposure and respiratory symptoms in adults has generally been inconclusive. This may be related in part to sample size issues, which also preclude analysis in potentially vulnerable subgroups.

Objectives:
We estimated associations between air pollution exposures and the prevalence of wheeze and shortness of breath using harmonized baseline data from two very large European cohorts, Lifelines (2006–2013) and UK Biobank (2006–2010). Our aim was also to determine whether the relationship between air pollution and respiratory symptom prevalence differed between individuals with different characteristics.

Conclusion:
Exposure to PM and NO2 air pollution was associated with the prevalence of wheeze and shortness of breath in this large study, with stronger associations between PM2.5 and both outcomes among lower- versus higher-income participants. https://doi.org/10.1289/EHP1353

Narrow-sense heritability (h2) is an important genetic parameter that quantifies the proportion of phenotypic variance in a trait attributable to the additive genetic variation generated by all causal variants. Estimation of h2 previously relied on closely related individuals, but recent developments allow estimation of the variance explained by all SNPs used in a genome-wide association study (GWAS) in conventionally unrelated individuals, that is, the SNP-based heritability ( ). In this Perspective, we discuss recently developed methods to estimate for a complex trait (and genetic correlation between traits) using individual-level or summary GWAS data. We discuss issues that could influence the accuracy of , definitions, assumptions and interpretations of the models, and pitfalls of misusing the methods and misinterpreting the models and results.

The prevalence of sleep disturbance is high and increasing. The study investigated whether active, former and passive smoking were associated with sleep disturbance.
Methods:

This cross-sectional study used data from the UK Biobank: a cohort study of 502 655 participants, of whom 498 208 provided self-reported data on smoking and sleep characteristics. Multivariable multinomial and logistic regression models were used to examine the associations between smoking and sleep disturbance.
Results:

The prevalence of sleep disturbance is high and increasing. The study investigated whether active, former and passive smoking were associated with sleep disturbance.
Methods:

This cross-sectional study used data from the UK Biobank: a cohort study of 502 655 participants, of whom 498 208 provided self-reported data on smoking and sleep characteristics. Multivariable multinomial and logistic regression models were used to examine the associations between smoking and sleep disturbance.
Results:

@article{Jani2017,
title = {Multimorbidity and comorbidity in atrial fibrillation and effects on survival: findings from UK biobank cohort},
author = { B. Jani and B. Nicholl and R. McQueenie and D. Connelly and P. Hanlon and K. Gallacher and D. Lee and F. Mair},
year = {2017},
date = {2017-08-29},
journal = {Heart Journal },
abstract = {Background: Atrial Fibrillation (AF) is the commonest sustained arrhythmia but the number and type of comorbid long-term health conditions (LTCs) and their impact on mortality, if any, among people with AF remains unknown.

Purpose: To examine the number and type of comorbid LTCs, and their associations with all-cause mortality in UK Biobank participants with AF.

Methods: Data were reviewed from 495,010 participants in UK Biobank, an anonymised community research cohort, aged between 40–69 years, recruited between 2006–2010 from across the UK. Self-reported comorbidities (n=42) were identified in 3651 people with AF. All-cause mortality was available for a median follow-up period of 7 years (Interquartile range 76 months to 93 months) by linking UK Biobank records with national mortality records. Hazard Ratios (HRs) examined associations between number and type of comorbid LTC and all-cause mortality. Results were adjusted for age, sex, socio-economic status, smoking and anti-coagulation status.

Results: 3651 participants (0.7% of the study population) reported AF; mean age of participants was 61.9 years. The rate of all-cause mortality in those with AF was 6.7% (248 participants) at 7 years. Nearly 79% of participants with AF reported having at least one other LTC, while 55% reported one other cardiometabolic condition. Among AF participants, those with 4 or more comorbidities had a 3.5 times higher risk of mortality than those with none. Comorbid heart failure was associated with significantly higher risk of all-cause mortality (HR 2.96; 95% confidence intervals (CI) 1.83–4.80), while presence of comorbid stroke was not associated with higher risk of mortality. Among non-cardiometabolic conditions, presence of COPD (HR 3.31; 95% CI 2.14–5.11) and osteoporosis (HR 3.13; 95% CI 1.63–6.01) were associated with a significantly higher risk of all-cause mortality.},
keywords = {14151, atrial fibrillation},
pubstate = {published},
tppubtype = {article}
}

Background: Atrial Fibrillation (AF) is the commonest sustained arrhythmia but the number and type of comorbid long-term health conditions (LTCs) and their impact on mortality, if any, among people with AF remains unknown.

Purpose: To examine the number and type of comorbid LTCs, and their associations with all-cause mortality in UK Biobank participants with AF.

Methods: Data were reviewed from 495,010 participants in UK Biobank, an anonymised community research cohort, aged between 40–69 years, recruited between 2006–2010 from across the UK. Self-reported comorbidities (n=42) were identified in 3651 people with AF. All-cause mortality was available for a median follow-up period of 7 years (Interquartile range 76 months to 93 months) by linking UK Biobank records with national mortality records. Hazard Ratios (HRs) examined associations between number and type of comorbid LTC and all-cause mortality. Results were adjusted for age, sex, socio-economic status, smoking and anti-coagulation status.

Results: 3651 participants (0.7% of the study population) reported AF; mean age of participants was 61.9 years. The rate of all-cause mortality in those with AF was 6.7% (248 participants) at 7 years. Nearly 79% of participants with AF reported having at least one other LTC, while 55% reported one other cardiometabolic condition. Among AF participants, those with 4 or more comorbidities had a 3.5 times higher risk of mortality than those with none. Comorbid heart failure was associated with significantly higher risk of all-cause mortality (HR 2.96; 95% confidence intervals (CI) 1.83–4.80), while presence of comorbid stroke was not associated with higher risk of mortality. Among non-cardiometabolic conditions, presence of COPD (HR 3.31; 95% CI 2.14–5.11) and osteoporosis (HR 3.13; 95% CI 1.63–6.01) were associated with a significantly higher risk of all-cause mortality.

@article{Camm2017,
title = {Impact of inflammatory interleukin-1 genotypes on risk of infection in UK Biobank},
author = { C.F. Camm and B. Casadei and J.C. Hopewell},
url = {https://academic.oup.com/eurheartj/article/38/suppl_1/ehx502.P1768/4088920/P1768Impact-of-inflammatory-interleukin-1},
year = {2017},
date = {2017-08-29},
journal = {European Heart Journal},
abstract = {Background: The interleukin-1 (IL-1) pathway may offer promise as a target for the prevention of cardiovascular disease. For example, the impact of Canakinumab, a monoclonal antibody targeting IL-1β, on cardiovascular events in those with raised C-reactive protein (CRP) post-myocardial infarction is soon to be reported. However, targeting the IL-1 pathway, which has a prominent role in the inflammatory cascade, may affect innate immunity and potentially increase the risk of serious infection. Mendelian randomization approaches allow us to explore the impact of IL-1 genotypes, with life-long effects on the IL-1 pathway, to elucidate the risk of potential adverse events of targeting IL-1.

Purpose: To examine the impact of pro-inflammatory IL-1 genotypes on risk of hospital reported infection.

Methods: Among 115,894 genotyped participants of European ancestry in the UK Biobank (UKB), an IL-1(+) composite genotype, associated with overexpression of IL-1β as well as elevated CRP, and IL-1(−) composite genotype, not associated with overexpression of IL-1β, was constructed from three single nucleotide polymorphisms (rs16944 and rs1143634 [both in IL-1β]:, and rs17561 [in IL-1α]). Incident reports of infection were identified from hospital episode statistics based on relevant ICD-10 codes, and considered by body system and infectious agent. Associations of the IL-1(+/−) composite genotypes with time to first incident infection were estimated using Cox proportional hazards models adjusted for age, sex, and 10 principle components.

Results: A total of 68,528 (59.1%) UKB participants had IL-1(+) genotypes, previously associated with a pro-inflammatory response. There were no significant differences between the IL-1(+) and IL-1(−) groups in baseline characteristics, including age, gender, body mass index, diabetes, hypertension and pre-existing coronary disease (p>0.05). Among genotyped individuals, with an average follow-up of 6.2 years, 8393 individuals had an infection associated with admission to hospital (with infection being the primary cause of admission for 81.5%). There was no association between IL1(+/−) group and risk of infection (Hazard Ratio: 1.00; 95% CI: 0.96 to 1.04, p=0.96). This null association was consistent across different sites of infection including respiratory (n=2514), genitourinary (n=2936), and gastrointestinal (n=2428). Furthermore, there was no association of IL1(+/−) genotype with specific infectious agents, including bacterial (n=4207), viral (n=725) or fungal (n=543).

Background: The interleukin-1 (IL-1) pathway may offer promise as a target for the prevention of cardiovascular disease. For example, the impact of Canakinumab, a monoclonal antibody targeting IL-1β, on cardiovascular events in those with raised C-reactive protein (CRP) post-myocardial infarction is soon to be reported. However, targeting the IL-1 pathway, which has a prominent role in the inflammatory cascade, may affect innate immunity and potentially increase the risk of serious infection. Mendelian randomization approaches allow us to explore the impact of IL-1 genotypes, with life-long effects on the IL-1 pathway, to elucidate the risk of potential adverse events of targeting IL-1.

Purpose: To examine the impact of pro-inflammatory IL-1 genotypes on risk of hospital reported infection.

Methods: Among 115,894 genotyped participants of European ancestry in the UK Biobank (UKB), an IL-1(+) composite genotype, associated with overexpression of IL-1β as well as elevated CRP, and IL-1(−) composite genotype, not associated with overexpression of IL-1β, was constructed from three single nucleotide polymorphisms (rs16944 and rs1143634 [both in IL-1β]:, and rs17561 [in IL-1α]). Incident reports of infection were identified from hospital episode statistics based on relevant ICD-10 codes, and considered by body system and infectious agent. Associations of the IL-1(+/−) composite genotypes with time to first incident infection were estimated using Cox proportional hazards models adjusted for age, sex, and 10 principle components.

Results: A total of 68,528 (59.1%) UKB participants had IL-1(+) genotypes, previously associated with a pro-inflammatory response. There were no significant differences between the IL-1(+) and IL-1(−) groups in baseline characteristics, including age, gender, body mass index, diabetes, hypertension and pre-existing coronary disease (p>0.05). Among genotyped individuals, with an average follow-up of 6.2 years, 8393 individuals had an infection associated with admission to hospital (with infection being the primary cause of admission for 81.5%). There was no association between IL1(+/−) group and risk of infection (Hazard Ratio: 1.00; 95% CI: 0.96 to 1.04, p=0.96). This null association was consistent across different sites of infection including respiratory (n=2514), genitourinary (n=2936), and gastrointestinal (n=2428). Furthermore, there was no association of IL1(+/−) genotype with specific infectious agents, including bacterial (n=4207), viral (n=725) or fungal (n=543).

Conclusions: This study suggests that lifelong predisposition to a pro-inflammatory response resulting from perturbation of the IL1 pathway is not associated with hospital reported infections. By contrast, Canakinumab has been associated with mildly increased rates of infection. Therefore, this genetic finding may reflect differences in pro-inflammatory versus inhibitory effects or potential biological compensation.

Purpose: This study describes characterization of brain WM microstructural features associated with HT from recently available brain magnetic resonance imaging in UK Biobank participants. We also explored interactions of HT with aging-associated brain changes.

Methods: 4501 subjects (62.2±7.3yrs, 53.1% of male) were included. UK Biobank brain image derived phenotype data provided WM microstructure measures (mean diffusivity (MD), fractional anisotropy (FA), and isotropic volume fraction (ISOVF)). HT was defined as SBP ≥140, DBP ≥90 mmHg or receiving HT medication. We first regressed WM microstructure measures onto HT correcting for age, sex, educational level, body mass index, ever smoked, diabetes mellitus, and cardiovascular disease using linear models (N=4501). We also conducted propensity score (PS) matching analysis. The participants were classified into two groups based on whether they had HT (HT group, N=2253) or not (non-HT group, N=2248). The subjects without HT group were matched in a 1:1 ratio with the HT group by variables used in the multiple linear models using the nearest neighbor method. After PS matching, we compared the resultant two groups (N=1492, each) for each of the WM microstructure measures. Finally, we examined an interaction of HT for an association of WM microstructure measures with age using analysis of covariance in the PS matching cohort (N=2984). All hypothesis testing was 2-sided with a significance level of P<0.05 after Bonferroni correction.

Results: The multivariate linear models showed that HT was positively correlated with white matter MD (b=0.039, p=0.050) and ISOVF (b =0.051, p=0.005). PS matching produced similar distributions of baseline characteristics for HT and non-HT groups (p>0.05), and consistent results with those of multivariate linear models: white matter FA was lower (p=0.003), and MD (p=5.33E–9) and ISOVF (p=4.40E–12) were higher in the group with HT than that without HT. A significant interaction of HT was found between MD and age only for women (b=–0.071, p=0.027; men, b=–0.021, p=1.000); relative increases in MD with age were larger in women with HT than in those without.},
keywords = {brain, cardiovascular, hypertension},
pubstate = {published},
tppubtype = {article}
}

Background: Hypertension (HT) damages multiple organ systems including the brain, and is a leading cause of vascular cognitive impairment and a risk factor for dementia. Changes in white matter (WM) microstructures precede WM hyperintensities and may predict future dementia in people at risk.

Purpose: This study describes characterization of brain WM microstructural features associated with HT from recently available brain magnetic resonance imaging in UK Biobank participants. We also explored interactions of HT with aging-associated brain changes.

Methods: 4501 subjects (62.2±7.3yrs, 53.1% of male) were included. UK Biobank brain image derived phenotype data provided WM microstructure measures (mean diffusivity (MD), fractional anisotropy (FA), and isotropic volume fraction (ISOVF)). HT was defined as SBP ≥140, DBP ≥90 mmHg or receiving HT medication. We first regressed WM microstructure measures onto HT correcting for age, sex, educational level, body mass index, ever smoked, diabetes mellitus, and cardiovascular disease using linear models (N=4501). We also conducted propensity score (PS) matching analysis. The participants were classified into two groups based on whether they had HT (HT group, N=2253) or not (non-HT group, N=2248). The subjects without HT group were matched in a 1:1 ratio with the HT group by variables used in the multiple linear models using the nearest neighbor method. After PS matching, we compared the resultant two groups (N=1492, each) for each of the WM microstructure measures. Finally, we examined an interaction of HT for an association of WM microstructure measures with age using analysis of covariance in the PS matching cohort (N=2984). All hypothesis testing was 2-sided with a significance level of P<0.05 after Bonferroni correction.

Results: The multivariate linear models showed that HT was positively correlated with white matter MD (b=0.039, p=0.050) and ISOVF (b =0.051, p=0.005). PS matching produced similar distributions of baseline characteristics for HT and non-HT groups (p>0.05), and consistent results with those of multivariate linear models: white matter FA was lower (p=0.003), and MD (p=5.33E–9) and ISOVF (p=4.40E–12) were higher in the group with HT than that without HT. A significant interaction of HT was found between MD and age only for women (b=–0.071, p=0.027; men, b=–0.021, p=1.000); relative increases in MD with age were larger in women with HT than in those without.

Results: The studied cohort was 61±8 years old and 46% male. The mean±SD of SBP and CMR-derived LV mass were 136±18mmHg and 89±24g, respectively. In univariate analysis, every 10mmHg increase in SBP was associated with 4.3g (95% CI 3.9 to 4.7g, p<10–16, adjusted R-squared 0.10) higher LV mass. In multivariate analysis, we observed 2.4g (95% CI 2.0 to 2.7g, p<10–16, adjusted R-squared 0.63) greater LV mass for every 10mmHg increment in SBP. Age was a significant effect modifier for the relationship between SBP and LV mass – every decade increase in age was associated with -0.9g (95% CI -1.4 to -4.2g, p for interaction = 0.0002) difference in LV mass per 10mmHg increase in SBP (Figure 1).

Conclusions: We confirmed a strong positive correlation between SBP and LV mass after adjusting for potential confounders in a large community-based cohort. The effect of SBP on LV mass was blunted by older age, possibly due to myocardial fibrosis from ageing and prolonged exposure to high blood pressure. This finding suggests that surveillance of LV hypertrophy alone for cardiac end-organ damage may not truly reflect the disease progression in the elderly.},
keywords = {blood pressure, cardiac disease},
pubstate = {published},
tppubtype = {article}
}

Introduction: Left ventricular (LV) hypertrophy is a recognised complication of arterial hypertension and associated with deleterious prognosis. Surveillance of LV hypertrophy with either electrocardiogram or an imaging modality is an important component of hypertension management. Both ageing and prolonged exposure to hypertension can induce diffuse fibrosis of myocardium and potentially modify the relationship between systolic blood pressure (SBP) and LV mass.

Purpose: The aim of this study was to investigate the influence of age on association between SBP and LV mass.

Results: The studied cohort was 61±8 years old and 46% male. The mean±SD of SBP and CMR-derived LV mass were 136±18mmHg and 89±24g, respectively. In univariate analysis, every 10mmHg increase in SBP was associated with 4.3g (95% CI 3.9 to 4.7g, p<10–16, adjusted R-squared 0.10) higher LV mass. In multivariate analysis, we observed 2.4g (95% CI 2.0 to 2.7g, p<10–16, adjusted R-squared 0.63) greater LV mass for every 10mmHg increment in SBP. Age was a significant effect modifier for the relationship between SBP and LV mass – every decade increase in age was associated with -0.9g (95% CI -1.4 to -4.2g, p for interaction = 0.0002) difference in LV mass per 10mmHg increase in SBP (Figure 1).

Conclusions: We confirmed a strong positive correlation between SBP and LV mass after adjusting for potential confounders in a large community-based cohort. The effect of SBP on LV mass was blunted by older age, possibly due to myocardial fibrosis from ageing and prolonged exposure to high blood pressure. This finding suggests that surveillance of LV hypertrophy alone for cardiac end-organ damage may not truly reflect the disease progression in the elderly.

Background: Observational studies have demonstrated that increased bone mineral density is associated with a higher risk of type 2 diabetes (T2D), but the relationship with risk of coronary heart disease (CHD) is less clear. Moreover, substantial uncertainty remains about the causal relevance of increased bone mineral density for T2D and CHD, which can be assessed by Mendelian randomisation studies. Methods: We identified 235 independent single nucleotide polymorphisms (SNPs) associated at p<5×10 -8 with estimated heel bone mineral density (eBMD) in 116,501 individuals from the UK Biobank study, accounting for 13.9% of eBMD variance. For each eBMD-associated SNP, we extracted effect estimates from the largest available GWAS studies for T2D (DIAGRAM: n=26,676 T2D cases and 132,532 controls) and CHD (CARDIoGRAMplusC4D: n=60,801 CHD cases and 123,504 controls). A two-sample design using several Mendelian randomization approaches was used to investigate the causal relevance of eBMD for risk of T2D and CHD. In addition, we explored the relationship of eBMD, instrumented by the 235 SNPs, on 12 cardiovascular and metabolic risk factors. Finally, we conducted Mendelian randomization analysis in the reverse direction to investigate reverse causality. Results: Each one standard deviation increase in genetically instrumented eBMD (equivalent to 0.14 g/cm 2) was associated with an 8% higher risk of T2D (odds ratio [OR] 1.08; 95% confidence interval [CI]: 1.02 to 1.14; p=0.012) and 5% higher risk of CHD (OR 1.05; 95%CI: 1.00 to 1.10; p=0.034). Consistent results were obtained in sensitivity analyses using several different Mendelian randomization approaches. Equivalent increases in eBMD were also associated with lower plasma levels of HDL-cholesterol and increased insulin resistance. Mendelian randomization in the reverse direction using 94 T2D SNPs or 52 CHD SNPs showed no evidence of reverse causality with eBMD. Conclusions: These findings suggest a causal relationship between elevated bone mineral density with risks of both T2D and CHD.

@article{Gupta2017b,
title = {Ventilatory function as a predictor of mortality in lifelong non-smokers: evidence from large British cohort studies},
author = {Ramyani P Gupta and David P Strachan},
url = {http://bmjopen.bmj.com/content/bmjopen/7/7/e015381.full.pdf},
year = {2017},
date = {2017-08-21},
abstract = {Background
Reduced ventilatory function is an established predictor of all-cause mortality in general population cohorts. We sought to verify this in lifelong non-smokers, among whom confounding by active smoking can be excluded, and investigate associations with circulatory and cancer deaths.

Methods
In UK Biobank, among 149 343 white never-smokers aged 40–69 years at entry, 2401 deaths occurred over a mean of 6.5-year follow-up. In the Health Surveys for England (HSE) 1995, 1996, 2001 and Scottish Health Surveys (SHS) 1998 and 2003 combined, there were 500 deaths among 6579 white never-smokers aged 40–69 years at entry, followed for a mean of 13.9 years. SD (z) scores for forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) were derived using Global Lung Initiative 2012 reference equations. These z-scores were related to deaths from all causes, circulatory disease and cancers using proportional hazards models adjusted for age, sex, height, socioeconomic
status, region and survey.

Results
In the HSE–SHS data set, decreasing z-scores for FEV1 (zFEV1) and FVC (zFVC) were each associated to a similar degree with increased all-cause mortality (hazard ratios per unit decrement 1.17, 95% CI 1.09 to 1.25 for zFEV1 and 1.19, 95% CI 1.10 to 1.28 for zFVC). This was replicated in Biobank (HRs 1.21, 95% CI 1.17 to 1.26 and 1.24, 1.19 to 1.29, respectively). zFEV1 and zFVC were less strongly associated with mortality from circulatory diseases in HSE–SHS (HR 1.22, 95% CI 1.06 to 1.40 for zFVC) than in Biobank (HR 1.47, 95% CI 1.35 to 1.60 for zFVC). For cancer mortality, HRs were more consistent between cohorts (for zFVC: HRs 1.12, 95% CI 1.01 to 1.24 in HSE–SHS and 1.10, 1.05 to 1.15 in Biobank). The strongest associations were with respiratory mortality (for zFVC: HRs 1.61, 95% CI 1.25 to 2.08 in HSE–SHS and 2.15, 1.77 to 2.61 in Biobank).

Background
Reduced ventilatory function is an established predictor of all-cause mortality in general population cohorts. We sought to verify this in lifelong non-smokers, among whom confounding by active smoking can be excluded, and investigate associations with circulatory and cancer deaths.

Methods
In UK Biobank, among 149 343 white never-smokers aged 40–69 years at entry, 2401 deaths occurred over a mean of 6.5-year follow-up. In the Health Surveys for England (HSE) 1995, 1996, 2001 and Scottish Health Surveys (SHS) 1998 and 2003 combined, there were 500 deaths among 6579 white never-smokers aged 40–69 years at entry, followed for a mean of 13.9 years. SD (z) scores for forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) were derived using Global Lung Initiative 2012 reference equations. These z-scores were related to deaths from all causes, circulatory disease and cancers using proportional hazards models adjusted for age, sex, height, socioeconomic
status, region and survey.

Results
In the HSE–SHS data set, decreasing z-scores for FEV1 (zFEV1) and FVC (zFVC) were each associated to a similar degree with increased all-cause mortality (hazard ratios per unit decrement 1.17, 95% CI 1.09 to 1.25 for zFEV1 and 1.19, 95% CI 1.10 to 1.28 for zFVC). This was replicated in Biobank (HRs 1.21, 95% CI 1.17 to 1.26 and 1.24, 1.19 to 1.29, respectively). zFEV1 and zFVC were less strongly associated with mortality from circulatory diseases in HSE–SHS (HR 1.22, 95% CI 1.06 to 1.40 for zFVC) than in Biobank (HR 1.47, 95% CI 1.35 to 1.60 for zFVC). For cancer mortality, HRs were more consistent between cohorts (for zFVC: HRs 1.12, 95% CI 1.01 to 1.24 in HSE–SHS and 1.10, 1.05 to 1.15 in Biobank). The strongest associations were with respiratory mortality (for zFVC: HRs 1.61, 95% CI 1.25 to 2.08 in HSE–SHS and 2.15, 1.77 to 2.61 in Biobank).

Conclusions
Spirometric indices predicted mortality more strongly than systolic blood pressure or body mass index, emphasising the importance of promoting lung health in the general population, even among lifelong non-smokers.

To quantify the association of self-reported walking pace and handgrip strength with all-cause, cardiovascular, and cancer mortality.

Methods and results

A total of 230 670 women and 190 057 men free from prevalent cancer and cardiovascular disease were included from UK Biobank. Usual walking pace was self-defined as slow, steady/average or brisk. Handgrip strength was assessed by dynamometer. Cox-proportional hazard models were adjusted for social deprivation, ethnicity, employment, medications, alcohol use, diet, physical activity, and television viewing time. Interaction terms investigated whether age, body mass index (BMI), and smoking status modified associations. Over 6.3 years, there were 8598 deaths, 1654 from cardiovascular disease and 4850 from cancer. Associations of walking pace with mortality were modified by BMI. In women, the hazard ratio (HR) for all-cause mortality in slow compared with fast walkers were 2.16 [95% confidence interval (CI): 1.68–2.77] and 1.31 (1.08–1.60) in the bottom and top BMI tertiles, respectively; corresponding HRs for men were 2.01 (1.68–2.41) and 1.41 (1.20–1.66). Hazard ratios for cardiovascular mortality remained above 1.7 across all categories of BMI in men and women, with modest heterogeneity in men. Handgrip strength was associated with cardiovascular mortality in men only (HR tertile 1 vs. tertile 3 = 1.38; 1.18–1.62), without differences across BMI categories, while associations with all-cause mortality were only seen in men with low BMI. Associations for walking pace and handgrip strength with cancer mortality were less consistent.

To quantify the association of self-reported walking pace and handgrip strength with all-cause, cardiovascular, and cancer mortality.

Methods and results

A total of 230 670 women and 190 057 men free from prevalent cancer and cardiovascular disease were included from UK Biobank. Usual walking pace was self-defined as slow, steady/average or brisk. Handgrip strength was assessed by dynamometer. Cox-proportional hazard models were adjusted for social deprivation, ethnicity, employment, medications, alcohol use, diet, physical activity, and television viewing time. Interaction terms investigated whether age, body mass index (BMI), and smoking status modified associations. Over 6.3 years, there were 8598 deaths, 1654 from cardiovascular disease and 4850 from cancer. Associations of walking pace with mortality were modified by BMI. In women, the hazard ratio (HR) for all-cause mortality in slow compared with fast walkers were 2.16 [95% confidence interval (CI): 1.68–2.77] and 1.31 (1.08–1.60) in the bottom and top BMI tertiles, respectively; corresponding HRs for men were 2.01 (1.68–2.41) and 1.41 (1.20–1.66). Hazard ratios for cardiovascular mortality remained above 1.7 across all categories of BMI in men and women, with modest heterogeneity in men. Handgrip strength was associated with cardiovascular mortality in men only (HR tertile 1 vs. tertile 3 = 1.38; 1.18–1.62), without differences across BMI categories, while associations with all-cause mortality were only seen in men with low BMI. Associations for walking pace and handgrip strength with cancer mortality were less consistent.

Conclusion

A simple self-reported measure of slow walking pace could aid risk stratification for all-cause and cardiovascular mortality within the general population.